{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# -*- coding:utf-8 -*-\n",
    "import sys\n",
    "#reload(sys)\n",
    "#sys.setdefaultencoding(\"utf-8\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 波士顿房价数据探索\n",
    "该数据集来自UCI机器学习知识库。波士顿房屋这些数据于1978年开始统计，共506个数据点，涵盖了麻省波士顿不同郊区房屋13种特征和房价中位数的信息。 本项目将原始数据集存为csv格式，方便调用pandas做数据分析。\n",
    "\n",
    "在开始一项新任务时，通过可视化手段探索数据往往是任务的第一步，从而根据数据特点选择合适的数据预处理方式和机器学习模型。 相比直接阅读许多行原始数据，图表汇总数据能更好地帮助我们把握数据的要点。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CRIM</th>\n",
       "      <th>ZN</th>\n",
       "      <th>INDUS</th>\n",
       "      <th>CHAS</th>\n",
       "      <th>NOX</th>\n",
       "      <th>RM</th>\n",
       "      <th>AGE</th>\n",
       "      <th>DIS</th>\n",
       "      <th>RAD</th>\n",
       "      <th>TAX</th>\n",
       "      <th>PTRATIO</th>\n",
       "      <th>B</th>\n",
       "      <th>LSTAT</th>\n",
       "      <th>MEDV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.00632</td>\n",
       "      <td>18</td>\n",
       "      <td>2.31</td>\n",
       "      <td>0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>6.575</td>\n",
       "      <td>65.2</td>\n",
       "      <td>4.0900</td>\n",
       "      <td>1</td>\n",
       "      <td>296</td>\n",
       "      <td>15</td>\n",
       "      <td>396.90</td>\n",
       "      <td>4.98</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.02731</td>\n",
       "      <td>0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>6.421</td>\n",
       "      <td>78.9</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2</td>\n",
       "      <td>242</td>\n",
       "      <td>17</td>\n",
       "      <td>396.90</td>\n",
       "      <td>9.14</td>\n",
       "      <td>21.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.02729</td>\n",
       "      <td>0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>7.185</td>\n",
       "      <td>61.1</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2</td>\n",
       "      <td>242</td>\n",
       "      <td>17</td>\n",
       "      <td>392.83</td>\n",
       "      <td>4.03</td>\n",
       "      <td>34.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.03237</td>\n",
       "      <td>0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>6.998</td>\n",
       "      <td>45.8</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3</td>\n",
       "      <td>222</td>\n",
       "      <td>18</td>\n",
       "      <td>394.63</td>\n",
       "      <td>2.94</td>\n",
       "      <td>33.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.06905</td>\n",
       "      <td>0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>7.147</td>\n",
       "      <td>54.2</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3</td>\n",
       "      <td>222</td>\n",
       "      <td>18</td>\n",
       "      <td>396.90</td>\n",
       "      <td>5.33</td>\n",
       "      <td>36.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      CRIM  ZN  INDUS  CHAS    NOX     RM   AGE     DIS  RAD  TAX  PTRATIO  \\\n",
       "0  0.00632  18   2.31     0  0.538  6.575  65.2  4.0900    1  296       15   \n",
       "1  0.02731   0   7.07     0  0.469  6.421  78.9  4.9671    2  242       17   \n",
       "2  0.02729   0   7.07     0  0.469  7.185  61.1  4.9671    2  242       17   \n",
       "3  0.03237   0   2.18     0  0.458  6.998  45.8  6.0622    3  222       18   \n",
       "4  0.06905   0   2.18     0  0.458  7.147  54.2  6.0622    3  222       18   \n",
       "\n",
       "        B  LSTAT  MEDV  \n",
       "0  396.90   4.98  24.0  \n",
       "1  396.90   9.14  21.6  \n",
       "2  392.83   4.03  34.7  \n",
       "3  394.63   2.94  33.4  \n",
       "4  396.90   5.33  36.2  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "#处理csv文件\n",
    "import pandas as pd\n",
    "#画直方图用，对数据结果进行可视化\n",
    "import matplotlib.pyplot as plt\n",
    "#对matplotlib进行一次封装，画图更容易，使用更方便\n",
    "import seaborn as sns\n",
    "#波士顿房价预测\n",
    "data_path = \"/home/tianyu/software/IDEAProjects/machine_learning/data/boston_housing.csv\"\n",
    "\n",
    "#读取数据\n",
    "df = pd.read_csv(data_path)\n",
    "#显示前五行\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 506 entries, 0 to 505\n",
      "Data columns (total 14 columns):\n",
      "CRIM       506 non-null float64\n",
      "ZN         506 non-null int64\n",
      "INDUS      506 non-null float64\n",
      "CHAS       506 non-null int64\n",
      "NOX        506 non-null float64\n",
      "RM         506 non-null float64\n",
      "AGE        506 non-null float64\n",
      "DIS        506 non-null float64\n",
      "RAD        506 non-null int64\n",
      "TAX        506 non-null int64\n",
      "PTRATIO    506 non-null int64\n",
      "B          506 non-null float64\n",
      "LSTAT      506 non-null float64\n",
      "MEDV       506 non-null float64\n",
      "dtypes: float64(9), int64(5)\n",
      "memory usage: 55.5 KB\n"
     ]
    }
   ],
   "source": [
    "#数据的总体信息\n",
    "#一共包含多少个样本点，一共多少列，列的名字，非空数值，数据类型\n",
    "#X 需要是一个数值，方便处理，对字符串的需要进行编码，才能送到数据模型中\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['CRIM', 'ZN', 'INDUS', 'CHAS', 'NOX', 'RM', 'AGE', 'DIS', 'RAD', 'TAX',\n",
       "       'PTRATIO', 'B', 'LSTAT', 'MEDV'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#列名\n",
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(506, 14)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#形状\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 一、样本数N：506\n",
    "\n",
    "# 二、特征维数：13，每个特征的数据类型，非空值的样本数目\n",
    "\n",
    "CRIM：人均犯罪率 ；\n",
    "ZN：住宅用地的比例（对超过两万五千平方英尺的区域） ；整数\n",
    "INDUS：城镇中非零售营业比例；\n",
    "CHAS：是否靠近Charles河的边界；整数\n",
    "NOX：一氧化氮浓度 ；\n",
    "RM：住宅平均房间数；\n",
    "AGE：1940年之前建造的自住房屋的比例；\n",
    "DIS：距离波士顿五个中心的加权距离；\n",
    "RAD：高速公路的便利指数（索引）；整数\n",
    "TAX ：每一万美元财产的全额财产税率； 整数\n",
    "PTRATIO ：城乡师生比例；PTRATIO\n",
    "B ：黑人比例\n",
    "LSTAT ：低收入人群比例\n",
    "\n",
    "# 三、标签y\n",
    "MEDV ：自住房屋价格的中值"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据探索"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "查看数据个特征的分布，特征与标签（MEDV）之间的关系,特征与特征之间的关系(是否存在冗余)\n",
    "数据表的特征类型通常两种\n",
    "1. 数值型特征(int64 和 float64)\n",
    "2. 类别型特征(categorical features)或离散型特征，离散型特征具有固定数目的值，如果特征只有两个取值，也称为二元(binary)变量，如果类别型变量的值具有顺序，成为有序(ordinal)类别型变量\n",
    "\n",
    "借助可视化工具来直观感觉数据的分布\n",
    "在python中，数据可视化有很多种\n",
    "Matplotlib非常强大，但是复杂，不易于学习\n",
    "Seaborn是在matplotlib的基础上进行了更高级的API封装，从而使得作图更加容易，在大多数情况下使用seaborn就能做出很具有吸引力的图，而使用matplotlibn就行制作更具特色的图\n",
    "\n",
    "在Boston房价预测数据，所有特征居委数值型特征（RAD为告诉公路便利指数，亦可视为类别性特征，CHAS为0/1编码，为类别型特征）\n",
    "\n",
    "对数值型特征，describe方法可以特征的基本统计学特性，未缺失的数值，均值，标准差，范围，四分位数，中位数，四分之三分位数，最大值，最小值\n",
    "\n",
    "\n",
    "查看非数值型特征的统计数据时，需要通过include参数显示制定包含的数据类型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CRIM</th>\n",
       "      <th>ZN</th>\n",
       "      <th>INDUS</th>\n",
       "      <th>CHAS</th>\n",
       "      <th>NOX</th>\n",
       "      <th>RM</th>\n",
       "      <th>AGE</th>\n",
       "      <th>DIS</th>\n",
       "      <th>RAD</th>\n",
       "      <th>TAX</th>\n",
       "      <th>PTRATIO</th>\n",
       "      <th>B</th>\n",
       "      <th>LSTAT</th>\n",
       "      <th>MEDV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "      <td>506.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.613524</td>\n",
       "      <td>11.347826</td>\n",
       "      <td>11.136779</td>\n",
       "      <td>0.069170</td>\n",
       "      <td>0.554695</td>\n",
       "      <td>6.284634</td>\n",
       "      <td>68.574901</td>\n",
       "      <td>3.795043</td>\n",
       "      <td>9.549407</td>\n",
       "      <td>408.237154</td>\n",
       "      <td>18.083004</td>\n",
       "      <td>356.674032</td>\n",
       "      <td>12.653063</td>\n",
       "      <td>22.532806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>8.601545</td>\n",
       "      <td>23.310593</td>\n",
       "      <td>6.860353</td>\n",
       "      <td>0.253994</td>\n",
       "      <td>0.115878</td>\n",
       "      <td>0.702617</td>\n",
       "      <td>28.148861</td>\n",
       "      <td>2.105710</td>\n",
       "      <td>8.707259</td>\n",
       "      <td>168.537116</td>\n",
       "      <td>2.280574</td>\n",
       "      <td>91.294864</td>\n",
       "      <td>7.141062</td>\n",
       "      <td>9.197104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.006320</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.460000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.385000</td>\n",
       "      <td>3.561000</td>\n",
       "      <td>2.900000</td>\n",
       "      <td>1.129600</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>187.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>0.320000</td>\n",
       "      <td>1.730000</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.082045</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.190000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.449000</td>\n",
       "      <td>5.885500</td>\n",
       "      <td>45.025000</td>\n",
       "      <td>2.100175</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>279.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>375.377500</td>\n",
       "      <td>6.950000</td>\n",
       "      <td>17.025000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.256510</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.690000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.538000</td>\n",
       "      <td>6.208500</td>\n",
       "      <td>77.500000</td>\n",
       "      <td>3.207450</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>330.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>391.440000</td>\n",
       "      <td>11.360000</td>\n",
       "      <td>21.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3.677082</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>18.100000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.624000</td>\n",
       "      <td>6.623500</td>\n",
       "      <td>94.075000</td>\n",
       "      <td>5.188425</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>666.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>396.225000</td>\n",
       "      <td>16.955000</td>\n",
       "      <td>25.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>88.976200</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>27.740000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.871000</td>\n",
       "      <td>8.780000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>12.126500</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>711.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>396.900000</td>\n",
       "      <td>37.970000</td>\n",
       "      <td>50.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             CRIM          ZN       INDUS        CHAS         NOX          RM  \\\n",
       "count  506.000000  506.000000  506.000000  506.000000  506.000000  506.000000   \n",
       "mean     3.613524   11.347826   11.136779    0.069170    0.554695    6.284634   \n",
       "std      8.601545   23.310593    6.860353    0.253994    0.115878    0.702617   \n",
       "min      0.006320    0.000000    0.460000    0.000000    0.385000    3.561000   \n",
       "25%      0.082045    0.000000    5.190000    0.000000    0.449000    5.885500   \n",
       "50%      0.256510    0.000000    9.690000    0.000000    0.538000    6.208500   \n",
       "75%      3.677082   12.000000   18.100000    0.000000    0.624000    6.623500   \n",
       "max     88.976200  100.000000   27.740000    1.000000    0.871000    8.780000   \n",
       "\n",
       "              AGE         DIS         RAD         TAX     PTRATIO           B  \\\n",
       "count  506.000000  506.000000  506.000000  506.000000  506.000000  506.000000   \n",
       "mean    68.574901    3.795043    9.549407  408.237154   18.083004  356.674032   \n",
       "std     28.148861    2.105710    8.707259  168.537116    2.280574   91.294864   \n",
       "min      2.900000    1.129600    1.000000  187.000000   12.000000    0.320000   \n",
       "25%     45.025000    2.100175    4.000000  279.000000   17.000000  375.377500   \n",
       "50%     77.500000    3.207450    5.000000  330.000000   19.000000  391.440000   \n",
       "75%     94.075000    5.188425   24.000000  666.000000   20.000000  396.225000   \n",
       "max    100.000000   12.126500   24.000000  711.000000   22.000000  396.900000   \n",
       "\n",
       "            LSTAT        MEDV  \n",
       "count  506.000000  506.000000  \n",
       "mean    12.653063   22.532806  \n",
       "std      7.141062    9.197104  \n",
       "min      1.730000    5.000000  \n",
       "25%      6.950000   17.025000  \n",
       "50%     11.360000   21.200000  \n",
       "75%     16.955000   25.000000  \n",
       "max     37.970000   50.000000  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#对数值型特征，得到每个特征的描述统计量\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "做数据特征分析，先看单个变量/特征的分布\n",
    "对单个变量，用直方图、箱体图等方式查看其大致分布，是否存在噪声数据点等\n",
    "\n",
    "对数字型特征可以调用seaborn的displot方法对其进行画图 displot（distribution plot）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#seaborn的distplot方法可以对数值型特征回执直方图（distribution plot）\n",
    "#目标 y (房屋价格中位数)的直方图/分布\n",
    "fig = plt.figure()\n",
    "#bins 表示等分成多少分，整个数值的取值空间，等分成多少分\n",
    "#kde表示是否进行和密度估计，只用直方图判断分布的话不够平滑，使用kde可以得到平滑的分布\n",
    "#和密度估计是直方图的一个平滑版本\n",
    "#右边房价高的地方更多一点，大致符合正态分布\n",
    "#右边的数据不太正常，算是噪声？后面处理的时候可以处理掉\n",
    "sns.distplot(df[\"MEDV\"], bins = 30, kde=True)\n",
    "plt.xlabel(\"Median value of owner-occupied homes\", fontsize = 12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以看出，标签y主要接种在20附近，和正太分布比较接近，但是较小的值比较集中，较大的值比较分散（长尾）,取值为最大值50的样本数比较多(猜测是对大值做了阶段)，在训练模型时可以考虑讲y等于50的样本当成outliers（离群点）去掉，纵轴为归一化后的值(概率密度)，每个分布在整体中所占的概率，总的概率之和为1\n",
    "\n",
    "对价格类特征，统计人多数值的敏感程度不是线性的，可以考虑对其进行log变化(Numpy 的log1p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAD6CAYAAABamQdMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAATrUlEQVR4nO3dfZBd9X3f8fen4AeMUgTG3qGS2iU1doZYsWM2lAxpZ2XaRA4eiz88HihJREpH05a4tFHGBvcP2s4wJe0Q15m27iiBQZ5xWVNqBwY7jSlhQzMTcCU/iQdTq1jE0mBUj4FkHQZ3nW//2COzKyTt3fuwd/Xb92tGs+f8zrnnfO937v3o7Nlzz01VIUlqy18ZdwGSpOEz3CWpQYa7JDXIcJekBhnuktQgw12SGrRsuCe5M8nRJI8fN/7hJN9I8kSSf7to/OYkB5M8neQXRlG0JOnUzuxhnbuA/wB86thAkm3ADuBdVfVKkrd24xcDVwM/Cfw14H8keXtV/fBUOzj//PNrcnKyryewVnz/+9/n7LPPHncZa4b9WMp+vMpeLDVIP/bv3//dqnrLiZYtG+5V9UiSyeOG/zFwW1W90q1ztBvfAcx0499KchC4FPiTU+1jcnKSffv2LVfKmjY7O8v09PS4y1gz7MdS9uNV9mKpQfqR5NmTLev3nPvbgb+d5LEkf5TkZ7rxTcC3F613uBuTJK2iXk7LnOxx5wGXAT8D3JPkx1eygSS7gF0AExMTzM7O9lnK2jA3N3faP4dhsh9L2Y9X2YulRtWPfsP9MPDZWrgxzZeS/CVwPnAE2LJovc3d2GtU1R5gD8DU1FSd7r+m+avmUvZjKfvxKnux1Kj60e9pmd8DtgEkeTvweuC7wP3A1UnekORC4CLgS8MoVJLUu2WP3JPcDUwD5yc5DNwC3Anc2V0e+QNgZ3cU/0SSe4AngXnghuWulJEkDV8vV8tcc5JFv3SS9W8Fbh2kKEnSYPyEqiQ1yHCXpAYZ7pLUoH4vhdQ6NXnT53tab/fWea7rcd1eHLrtyqFtS1oPPHKXpAYZ7pLUIMNdkhpkuEtSgwx3SWqQ4S5JDTLcJalBhrskNchwl6QGGe6S1CDDXZIaZLhLUoMMd0lqkOEuSQ1aNtyT3JnkaPd9qccv252kkpzfzSfJbyc5mOTrSd4ziqIlSafWy5H7XcD24weTbAF+HvjTRcPvAy7q/u0CPjl4iZKklVo23KvqEeB7J1j0ceAjQC0a2wF8qhY8CmxMcsFQKpUk9ayvc+5JdgBHquprxy3aBHx70fzhbkyStIpW/DV7Sd4EfIyFUzJ9S7KLhVM3TExMMDs7O8jmxm5ubu60fw692L11vqf1Js7qfd1enO69XS+vj17Yi6VG1Y9+vkP1bwIXAl9LArAZ+HKSS4EjwJZF627uxl6jqvYAewCmpqZqenq6j1LWjtnZWU7359CLXr8XdffWeW4/MLyv6D107fTQtjUO6+X10Qt7sdSo+rHi0zJVdaCq3lpVk1U1ycKpl/dU1XeA+4Ff6a6auQx4qaqeG27JkqTl9HIp5N3AnwDvSHI4yfWnWP0LwDPAQeB3gH8ylColSSuy7O/NVXXNMssnF00XcMPgZUmSBuEnVCWpQYa7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJapDhLkkNMtwlqUGGuyQ1yHCXpAYZ7pLUIMNdkhpkuEtSgwx3SWqQ4S5JDTLcJalBhrskNaiX71C9M8nRJI8vGvt3Sb6R5OtJPpdk46JlNyc5mOTpJL8wqsIlSSfXy5H7XcD248YeBN5ZVT8F/G/gZoAkFwNXAz/ZPeY/JTljaNVKknqybLhX1SPA944b+2JVzXezjwKbu+kdwExVvVJV3wIOApcOsV5JUg/OHMI2/gHwmW56Ewthf8zhbuw1kuwCdgFMTEwwOzs7hFLGZ25u7rR/Dr3YvXV++ZWAibN6X7cXp3tv18vroxf2YqlR9WOgcE/yL4B54NMrfWxV7QH2AExNTdX09PQgpYzd7Owsp/tz6MV1N32+p/V2b53n9gPDOHZYcOja6aFtaxzWy+ujF/ZiqVH1o+93X5LrgPcDV1RVdcNHgC2LVtvcjUmSVlFfl0Im2Q58BPhAVf3FokX3A1cneUOSC4GLgC8NXqYkaSWWPXJPcjcwDZyf5DBwCwtXx7wBeDAJwKNV9Y+q6okk9wBPsnC65oaq+uGoipckndiy4V5V15xg+I5TrH8rcOsgRUmSBuMnVCWpQYa7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJapDhLkkNMtwlqUGGuyQ1yHCXpAYZ7pLUIMNdkhpkuEtSgwx3SWqQ4S5JDTLcJalBhrskNWjZcE9yZ5KjSR5fNHZekgeTfLP7eW43niS/neRgkq8nec8oi5cknVgvR+53AduPG7sJeKiqLgIe6uYB3gdc1P3bBXxyOGVKklZi2XCvqkeA7x03vAPY203vBa5aNP6pWvAosDHJBcMqVpLUm1TV8islk8ADVfXObv7FqtrYTQd4oao2JnkAuK2q/rhb9hDw0arad4Jt7mLh6J6JiYlLZmZmhvOMxmRubo4NGzaMu4yRO3DkpZ7WmzgLnn95ePvduumc4W1sDNbL66MX9mKpQfqxbdu2/VU1daJlZw5UFVBVlWT5/yFe+7g9wB6Aqampmp6eHrSUsZqdneV0fw69uO6mz/e03u6t89x+YOCX148cunZ6aNsah/Xy+uiFvVhqVP3o92qZ54+dbul+Hu3GjwBbFq23uRuTJK2ifsP9fmBnN70TuG/R+K90V81cBrxUVc8NWKMkaYWW/b05yd3ANHB+ksPALcBtwD1JrgeeBT7Urf4F4BeBg8BfAL86gpolSctYNtyr6pqTLLriBOsWcMOgRUmSBuMnVCWpQYa7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJapDhLkkNMtwlqUGGuyQ1yHCXpAYZ7pLUIMNdkhpkuEtSgwx3SWqQ4S5JDRreNxhLIzTZ4xdzj8Kh264c276lfnnkLkkNGijck/zzJE8keTzJ3UnemOTCJI8lOZjkM0leP6xiJUm96fu0TJJNwD8FLq6ql5PcA1zNwhdkf7yqZpL8Z+B64JNDqVbAeE9RSDo9DHpa5kzgrCRnAm8CngPeC9zbLd8LXDXgPiRJK5Sq6v/ByY3ArcDLwBeBG4FHq+pt3fItwO9X1TtP8NhdwC6AiYmJS2ZmZvquYy2Ym5tjw4YNq7KvA0deWpX9DGLiLHj+5XFXMRxbN50z8DZW8/Wx1tmLpQbpx7Zt2/ZX1dSJlg1yWuZcYAdwIfAi8F+B7b0+vqr2AHsApqamanp6ut9S1oTZ2VlW6zlcdxqcltm9dZ7bD7RxMdaha6cH3sZqvj7WOnux1Kj6Mchpmb8LfKuq/m9V/T/gs8DlwMbuNA3AZuDIgDVKklZokHD/U+CyJG9KEuAK4EngYeCD3To7gfsGK1GStFJ9h3tVPcbCH06/DBzotrUH+Cjw60kOAm8G7hhCnZKkFRjopGhV3QLcctzwM8Clg2xXkjQYP6EqSQ0y3CWpQYa7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJapDhLkkNMtwlqUGGuyQ1yHCXpAYZ7pLUIMNdkhpkuEtSgwx3SWqQ4S5JDTLcJalBA4V7ko1J7k3yjSRPJfnZJOcleTDJN7uf5w6rWElSbwY9cv8E8N+r6ieAdwFPATcBD1XVRcBD3bwkaRX1He5JzgH+DnAHQFX9oKpeBHYAe7vV9gJXDVqkJGllUlX9PTB5N7AHeJKFo/b9wI3Akara2K0T4IVj88c9fhewC2BiYuKSmZmZvupYK+bm5tiwYcOq7OvAkZdWZT+DmDgLnn953FUMx9ZN5wy8jdV8fax19mKpQfqxbdu2/VU1daJlg4T7FPAocHlVPZbkE8CfAR9eHOZJXqiqU553n5qaqn379vVVx1oxOzvL9PT0quxr8qbPr8p+BrF76zy3Hzhz3GUMxaHbrhx4G6v5+ljr7MVSg/QjyUnDfZBz7oeBw1X1WDd/L/Ae4PkkF3Q7vgA4OsA+JEl96Dvcq+o7wLeTvKMbuoKFUzT3Azu7sZ3AfQNVKElasUF/b/4w8OkkrweeAX6Vhf8w7klyPfAs8KEB9yFJWqGBwr2qvgqc6HzPFYNsV5I0GD+hKkkNauNyhjFZfNXK7q3zXHcaXMUiaX3wyF2SGmS4S1KDDHdJapDhLkkNMtwlqUGGuyQ1yHCXpAYZ7pLUIMNdkhpkuEtSgwx3SWqQ4S5JDTLcJalBhrskNchwl6QGGe6S1KCBwz3JGUm+kuSBbv7CJI8lOZjkM933q0qSVtEwjtxvBJ5aNP+bwMer6m3AC8D1Q9iHJGkFBvqavSSbgSuBW4FfTxLgvcDf71bZC/xL4JOD7Ecap8khfH1iP1/DeOi2Kwfer9avVFX/D07uBf4N8GPAbwDXAY92R+0k2QL8flW98wSP3QXsApiYmLhkZmam7zrG5cCRl340PXEWPP/yGItZY+zHUv30Y+umc0ZTzJjNzc2xYcOGcZexZgzSj23btu2vqqkTLev7yD3J+4GjVbU/yfRKH19Ve4A9AFNTUzU9veJNjN11x31B9u0H/L7xY+zHUv3049C106MpZsxmZ2c5Hd/vozKqfgzy7rsc+ECSXwTeCPxV4BPAxiRnVtU8sBk4MniZkqSV6PsPqlV1c1VtrqpJ4GrgD6vqWuBh4IPdajuB+wauUpK0IqO4zv2jLPxx9SDwZuCOEexDknQKQzkpWlWzwGw3/Qxw6TC2K0nqj59QlaQGGe6S1CDDXZIaZLhLUoMMd0lqkOEuSQ0y3CWpQd78Q1qjhnE3yn54N8o2eOQuSQ0y3CWpQYa7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJapDhLkkN6jvck2xJ8nCSJ5M8keTGbvy8JA8m+Wb389zhlStJ6sUgR+7zwO6quhi4DLghycXATcBDVXUR8FA3L0laRX2He1U9V1Vf7qb/HHgK2ATsAPZ2q+0Frhq0SEnSygzlxmFJJoGfBh4DJqrquW7Rd4CJYezjZMZ1cyVJ7Rhnjty1/eyRbDdVNdgGkg3AHwG3VtVnk7xYVRsXLX+hql5z3j3JLmAXwMTExCUzMzN97f/AkZf6K3zIJs6C518edxVrh/1Y6nTqx9ZN54x0+3Nzc2zYsGGk+1ipcebIheec0Xc/tm3btr+qpk60bKBwT/I64AHgD6rqt7qxp4HpqnouyQXAbFW941TbmZqaqn379vVVw1o5ct+9dZ7bD3gH5WPsx1KnUz9Gfcvf2dlZpqenR7qPlRr3kXu//Uhy0nAf5GqZAHcATx0L9s79wM5ueidwX7/7kCT1Z5BDicuBXwYOJPlqN/Yx4DbgniTXA88CHxqsREnSSvUd7lX1x0BOsviKfrcrSRqcn1CVpAYZ7pLUIMNdkhpkuEtSgwx3SWqQ4S5JDTLcJalBhrskNej0uNmFpHVhrdwrqgUeuUtSgwx3SWqQp2UkLTHqUyO7t85znadfRs4jd0lqkOEuSQ0y3CWpQYa7JDXIcJekBhnuktSgkYV7ku1Jnk5yMMlNo9qPJOm1RhLuSc4A/iPwPuBi4JokF49iX5Kk1xrVkfulwMGqeqaqfgDMADtGtC9J0nFGFe6bgG8vmj/cjUmSVkGqavgbTT4IbK+qf9jN/zLwt6rq1xatswvY1c2+A3h66IWsrvOB7467iDXEfixlP15lL5YapB9/o6recqIFo7q3zBFgy6L5zd3Yj1TVHmDPiPa/6pLsq6qpcdexVtiPpezHq+zFUqPqx6hOy/wv4KIkFyZ5PXA1cP+I9iVJOs5Ijtyraj7JrwF/AJwB3FlVT4xiX5Kk1xrZLX+r6gvAF0a1/TWomVNMQ2I/lrIfr7IXS42kHyP5g6okaby8/YAkNchw70OSO5McTfL4orHzkjyY5Jvdz3PHWeNqSbIlycNJnkzyRJIbu/H12o83JvlSkq91/fhX3fiFSR7rbsfxme5Cg3UhyRlJvpLkgW5+PffiUJIDSb6aZF83NpL3iuHen7uA7ceN3QQ8VFUXAQ918+vBPLC7qi4GLgNu6G41sV778Qrw3qp6F/BuYHuSy4DfBD5eVW8DXgCuH2ONq+1G4KlF8+u5FwDbqurdiy5/HMl7xXDvQ1U9AnzvuOEdwN5uei9w1aoWNSZV9VxVfbmb/nMW3sSbWL/9qKqa62Zf1/0r4L3Avd34uulHks3AlcDvdvNhnfbiFEbyXjHch2eiqp7rpr8DTIyzmHFIMgn8NPAY67gf3WmIrwJHgQeB/wO8WFXz3Srr6XYc/x74CPCX3fybWb+9gIX/6L+YZH/3KX0Y0XtlZJdCrmdVVUnW1WVISTYA/w34Z1X1ZwsHaAvWWz+q6ofAu5NsBD4H/MSYSxqLJO8HjlbV/iTT465njfi5qjqS5K3Ag0m+sXjhMN8rHrkPz/NJLgDofh4dcz2rJsnrWAj2T1fVZ7vhdduPY6rqReBh4GeBjUmOHUy95nYcjboc+ECSQyzcGfa9wCdYn70AoKqOdD+PsvAf/6WM6L1iuA/P/cDObnoncN8Ya1k13TnUO4Cnquq3Fi1ar/14S3fETpKzgL/Hwt8hHgY+2K22LvpRVTdX1eaqmmThFiR/WFXXsg57AZDk7CQ/dmwa+HngcUb0XvFDTH1IcjcwzcLd3J4HbgF+D7gH+OvAs8CHqur4P7o2J8nPAf8TOMCr51U/xsJ59/XYj59i4Y9iZ7Bw8HRPVf3rJD/OwtHrecBXgF+qqlfGV+nq6k7L/EZVvX+99qJ73p/rZs8E/ktV3ZrkzYzgvWK4S1KDPC0jSQ0y3CWpQYa7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJatD/B/SX6NRm9ly6AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#当然也可以使用dataframe的hist方法画房价中位数直方图\n",
    "hist = df['MEDV'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#使用DataFrame的hist()方法也可以绘制直方图(histogram)\n",
    "#displot绘图的纵轴为样本的比例，hist方法绘图的纵轴为样本数目\n",
    "#可以一次多个特征\n",
    "features = [\"MEDV\", \"CRIM\"]\n",
    "hist = df[features].hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "箱体图 boxplot & 提琴行图Violinplot\n",
    "\n",
    "箱型图可以可视化特征的分位数等统计量，主要用于离群点的返现，其主要组成部分是箱子(box)，须（whisker）和一些单独的数据点（离群值）\n",
    "\n",
    "箱子展示了分布的四分位距，他的长度由25%（Q1,下四分位数）和 75%（Q3,上四分位数）决定，箱子的水平线表示中位数(50%)\n",
    "\n",
    "从箱子外延伸出来的线被称为须，表示数据点的总体散步，即位于区间(Q1 - 1.5 x IQR, Q3 + 1.5 x IQR)的数据点，其中IQR是四分位距： IQR = Q3 - Q1\n",
    "\n",
    "离群值是须之外的数据点，他们为单独的数据点，沿着中轴回执\n",
    "\n",
    "Villinplot结合了箱型图与核密度估计图的特点，可以用一个或多个分量变量的情况下，连续变量数据的分布进行比较，Villinplot还可以用于观察多个数据分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function subplots in module matplotlib.pyplot:\n",
      "\n",
      "subplots(nrows=1, ncols=1, sharex=False, sharey=False, squeeze=True, subplot_kw=None, gridspec_kw=None, **fig_kw)\n",
      "    Create a figure and a set of subplots.\n",
      "    \n",
      "    This utility wrapper makes it convenient to create common layouts of\n",
      "    subplots, including the enclosing figure object, in a single call.\n",
      "    \n",
      "    Parameters\n",
      "    ----------\n",
      "    nrows, ncols : int, optional, default: 1\n",
      "        Number of rows/columns of the subplot grid.\n",
      "    \n",
      "    sharex, sharey : bool or {'none', 'all', 'row', 'col'}, default: False\n",
      "        Controls sharing of properties among x (`sharex`) or y (`sharey`)\n",
      "        axes:\n",
      "    \n",
      "            - True or 'all': x- or y-axis will be shared among all\n",
      "              subplots.\n",
      "            - False or 'none': each subplot x- or y-axis will be\n",
      "              independent.\n",
      "            - 'row': each subplot row will share an x- or y-axis.\n",
      "            - 'col': each subplot column will share an x- or y-axis.\n",
      "    \n",
      "        When subplots have a shared x-axis along a column, only the x tick\n",
      "        labels of the bottom subplot are created. Similarly, when subplots\n",
      "        have a shared y-axis along a row, only the y tick labels of the first\n",
      "        column subplot are created. To later turn other subplots' ticklabels\n",
      "        on, use `~matplotlib.axes.Axes.tick_params`.\n",
      "    \n",
      "    squeeze : bool, optional, default: True\n",
      "        - If True, extra dimensions are squeezed out from the returned\n",
      "          array of `~matplotlib.axes.Axes`:\n",
      "    \n",
      "            - if only one subplot is constructed (nrows=ncols=1), the\n",
      "              resulting single Axes object is returned as a scalar.\n",
      "            - for Nx1 or 1xM subplots, the returned object is a 1D numpy\n",
      "              object array of Axes objects.\n",
      "            - for NxM, subplots with N>1 and M>1 are returned as a 2D array.\n",
      "    \n",
      "        - If False, no squeezing at all is done: the returned Axes object is\n",
      "          always a 2D array containing Axes instances, even if it ends up\n",
      "          being 1x1.\n",
      "    \n",
      "    num : integer or string, optional, default: None\n",
      "        A `.pyplot.figure` keyword that sets the figure number or label.\n",
      "    \n",
      "    subplot_kw : dict, optional\n",
      "        Dict with keywords passed to the\n",
      "        `~matplotlib.figure.Figure.add_subplot` call used to create each\n",
      "        subplot.\n",
      "    \n",
      "    gridspec_kw : dict, optional\n",
      "        Dict with keywords passed to the `~matplotlib.gridspec.GridSpec`\n",
      "        constructor used to create the grid the subplots are placed on.\n",
      "    \n",
      "    **fig_kw\n",
      "        All additional keyword arguments are passed to the\n",
      "        `.pyplot.figure` call.\n",
      "    \n",
      "    Returns\n",
      "    -------\n",
      "    fig : `~.figure.Figure`\n",
      "    \n",
      "    ax : `.axes.Axes` object or array of Axes objects.\n",
      "        *ax* can be either a single `~matplotlib.axes.Axes` object or an\n",
      "        array of Axes objects if more than one subplot was created.  The\n",
      "        dimensions of the resulting array can be controlled with the squeeze\n",
      "        keyword, see above.\n",
      "    \n",
      "    Examples\n",
      "    --------\n",
      "    ::\n",
      "    \n",
      "        # First create some toy data:\n",
      "        x = np.linspace(0, 2*np.pi, 400)\n",
      "        y = np.sin(x**2)\n",
      "    \n",
      "        # Creates just a figure and only one subplot\n",
      "        fig, ax = plt.subplots()\n",
      "        ax.plot(x, y)\n",
      "        ax.set_title('Simple plot')\n",
      "    \n",
      "        # Creates two subplots and unpacks the output array immediately\n",
      "        f, (ax1, ax2) = plt.subplots(1, 2, sharey=True)\n",
      "        ax1.plot(x, y)\n",
      "        ax1.set_title('Sharing Y axis')\n",
      "        ax2.scatter(x, y)\n",
      "    \n",
      "        # Creates four polar axes, and accesses them through the returned array\n",
      "        fig, axes = plt.subplots(2, 2, subplot_kw=dict(polar=True))\n",
      "        axes[0, 0].plot(x, y)\n",
      "        axes[1, 1].scatter(x, y)\n",
      "    \n",
      "        # Share a X axis with each column of subplots\n",
      "        plt.subplots(2, 2, sharex='col')\n",
      "    \n",
      "        # Share a Y axis with each row of subplots\n",
      "        plt.subplots(2, 2, sharey='row')\n",
      "    \n",
      "        # Share both X and Y axes with all subplots\n",
      "        plt.subplots(2, 2, sharex='all', sharey='all')\n",
      "    \n",
      "        # Note that this is the same as\n",
      "        plt.subplots(2, 2, sharex=True, sharey=True)\n",
      "    \n",
      "        # Creates figure number 10 with a single subplot\n",
      "        # and clears it if it already exists.\n",
      "        fig, ax=plt.subplots(num=10, clear=True)\n",
      "    \n",
      "    See Also\n",
      "    --------\n",
      "    .pyplot.figure\n",
      "    .pyplot.subplot\n",
      "    .pyplot.axes\n",
      "    .Figure.subplots\n",
      "    .Figure.add_subplot\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(plt.subplots)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#\n",
    "_, axes = plt.subplots(1, 2, sharey=True, figsize=(6, 4))\n",
    "\n",
    "sns.boxplot(data=df[\"MEDV\"], ax=axes[0]); \n",
    "\n",
    "sns.violinplot(data=df[\"MEDV\"], ax=axes[1]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(df[\"CRIM\"], bins=30, kde=False)\n",
    "plt.xlabel(\"crime rate\", fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "大部分的犯罪率很小"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(df[\"ZN\"], bins=30, kde=False)\n",
    "plt.xlabel(\"proportion of residential land zoned\", fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAEJCAYAAABv6GdPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAV3klEQVR4nO3de5RlZX3m8e8DrYLgyK0WAzTYGFEHmUl0dRAvybAEJ8Q4wcwogkhA0R4nGElMAniZRWaiWWgSozPLcYYRFYwSGTSBmIyKREJ0FG0MUS4amnsTGhq5CSZR9Dd/7LfH00VVV9U5VRT19vezVq3a9/2+e5966j3v2WfvVBWSpL7ssNwFkCQtPsNdkjpkuEtShwx3SeqQ4S5JHVq13AUA2GuvvWrNmjXLXQxJWlGuvPLKu6tqaqZ5j4lwX7NmDevXr1/uYkjSipLkltnm2S0jSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6pDhLkkdekx8Q1XS+D5+xa3zWu5Vzz1giUuixxJb7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ3OGe5IPJbkrydUj034vybeSfCPJnyTZbWTeW5JsSPLtJD+3VAWXJM1uPi33jwBHTZt2CXBIVf0r4O+AtwAkORg4FnhWW+e/J9lx0UorSZqXOcO9qi4H7pk27XNV9XAb/Qqwug0fDfxxVf1TVd0EbAAOXcTySpLmYTH63F8L/J82vB9w28i8jW2aJOlRNFG4J3kb8DDwsTHWXZdkfZL1mzdvnqQYkqRpxg73JCcBLwWOr6pqk28H9h9ZbHWb9ghVdXZVra2qtVNTU+MWQ5I0g7HCPclRwGnAL1bV90ZmXQwcm+QJSQ4EDgK+OnkxJUkLsWquBZKcDxwO7JVkI3Amw9UxTwAuSQLwlap6Q1Vdk+QC4FqG7ppTquqHS1V4SdLM5gz3qjpuhsnnbGP5dwLvnKRQkqTJ+A1VSeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjo0Z7gn+VCSu5JcPTJtjySXJLm+/d69TU+S/5pkQ5JvJHnOUhZekjSz+bTcPwIcNW3aGcClVXUQcGkbB/h54KD2sw74wOIUU5K0EHOGe1VdDtwzbfLRwLlt+FzgZSPTz6vBV4DdkuyzWIWVJM3PuH3ue1fVHW14E7B3G94PuG1kuY1t2iMkWZdkfZL1mzdvHrMYkqSZTPyBalUVUGOsd3ZVra2qtVNTU5MWQ5I0Ytxwv3NLd0v7fVebfjuw/8hyq9s0SdKjaNxwvxg4sQ2fCFw0Mv2X21UzhwH3j3TfSJIeJavmWiDJ+cDhwF5JNgJnAmcBFyQ5GbgFOKYt/hfAS4ANwPeA1yxBmSVJc5gz3KvquFlmHTHDsgWcMmmhJEmT8RuqktQhw12SOmS4S1KHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQxOFe5JfT3JNkquTnJ9kpyQHJrkiyYYkn0jy+MUqrCRpfsYO9yT7AW8C1lbVIcCOwLHAu4A/rKqnAfcCJy9GQSVJ8zdpt8wqYOckq4AnAncALwIubPPPBV424T4kSQs0drhX1e3A7wO3MoT6/cCVwH1V9XBbbCOw30zrJ1mXZH2S9Zs3bx63GJKkGUzSLbM7cDRwILAvsAtw1HzXr6qzq2ptVa2dmpoatxiSpBlM0i1zJHBTVW2uqh8AnwJeAOzWumkAVgO3T1hGSdICTRLutwKHJXlikgBHANcCXwBe3pY5EbhosiJKkhZqkj73Kxg+OP068M22rbOB04E3J9kA7AmcswjllCQtwKq5F5ldVZ0JnDlt8o3AoZNsV5I0Gb+hKkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOmS4S1KHJgr3JLsluTDJt5Jcl+R5SfZIckmS69vv3RersJKk+Zm05f4+4DNV9UzgJ4HrgDOAS6vqIODSNi5JehSNHe5Jngz8LHAOQFV9v6ruA44Gzm2LnQu8bNJCSpIWZpKW+4HAZuDDSf4myQeT7ALsXVV3tGU2AXvPtHKSdUnWJ1m/efPmCYohSZpuknBfBTwH+EBVPRt4iGldMFVVQM20clWdXVVrq2rt1NTUBMWQJE03SbhvBDZW1RVt/EKGsL8zyT4A7fddkxVRkrRQY4d7VW0CbkvyjDbpCOBa4GLgxDbtROCiiUooSVqwVROu/6vAx5I8HrgReA3DP4wLkpwM3AIcM+E+JEkLNFG4V9VVwNoZZh0xyXYlSZPxG6qS1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShyZ9QPZ27eNX3Dqv5V713AOWuCSStDVb7pLUIcNdkjo0cbgn2THJ3yT5dBs/MMkVSTYk+USSx09eTEnSQixGy/1U4LqR8XcBf1hVTwPuBU5ehH1IkhZgonBPshr4BeCDbTzAi4AL2yLnAi+bZB+SpIWb9GqZ9wKnAU9q43sC91XVw218I7DfTCsmWQesAzjgAK8mWW5e+SP1ZeyWe5KXAndV1ZXjrF9VZ1fV2qpaOzU1NW4xJEkzmKTl/gLgF5O8BNgJ+GfA+4DdkqxqrffVwO2TF1OStBBjt9yr6i1Vtbqq1gDHAn9ZVccDXwBe3hY7Ebho4lJKkhZkKa5zPx14c5INDH3w5yzBPiRJ27Aotx+oqsuAy9rwjcChi7FdSdJ4/IaqJHXIcJekDnlXyBXIa9IlzcWWuyR1yHCXpA4Z7pLUIcNdkjpkuEtSh7xa5jFkvlfBSNJcbLlLUodsuUvaykLeQfpdiscuw11Lwi9aScvLbhlJ6tB21XK3NSlpe2HLXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ9vV1TLbG29nIG2/bLlLUocMd0nq0NjhnmT/JF9Icm2Sa5Kc2qbvkeSSJNe337svXnElSfMxScv9YeA3qupg4DDglCQHA2cAl1bVQcClbVyS9Cga+wPVqroDuKMNfzfJdcB+wNHA4W2xc4HLgNMnKuWjzA8iJa10i3K1TJI1wLOBK4C9W/ADbAL2nmWddcA6gAMO6PteLv6zkPRom/gD1SS7Ap8Efq2qHhidV1UF1EzrVdXZVbW2qtZOTU1NWgxJ0oiJwj3J4xiC/WNV9ak2+c4k+7T5+wB3TVZESdJCTXK1TIBzgOuq6j0jsy4GTmzDJwIXjV88SdI4JulzfwFwAvDNJFe1aW8FzgIuSHIycAtwzGRFlCQt1CRXy3wRyCyzjxh3u5KkyfkNVUnqkOEuSR3yrpBaVj7XdvvgeX702XKXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdchwl6QO+Q1VbZcW8nQsvzWplciWuyR1yHCXpA6t+G4ZHz4taVI93thsxYe7NMp/9tLAbhlJ6pAtd60Itsi10ix3V48td0nqkOEuSR2yW0ZaJMv9NlwaZctdkjq0ZOGe5Kgk306yIckZS7UfSdIjLUm4J9kReD/w88DBwHFJDl6KfUmSHmmpWu6HAhuq6saq+j7wx8DRS7QvSdI0qarF32jycuCoqnpdGz8BeG5VvXFkmXXAujb6DODb89j0XsDdi1zcxxLrt7L1XL+e6wYrt35PqaqpmWYs29UyVXU2cPZC1kmyvqrWLlGRlp31W9l6rl/PdYM+67dU3TK3A/uPjK9u0yRJj4KlCvevAQclOTDJ44FjgYuXaF+SpGmWpFumqh5O8kbgs8COwIeq6ppF2PSCunFWIOu3svVcv57rBh3Wb0k+UJUkLS+/oSpJHTLcJalDKybce7+dQZKbk3wzyVVJ1i93eSaV5ENJ7kpy9ci0PZJckuT69nv35SzjuGap228nub2dv6uSvGQ5yziJJPsn+UKSa5Nck+TUNr2X8zdb/bo5h7BC+tzb7Qz+DngxsJHhapzjquraZS3YIkpyM7C2qlbiFykeIcnPAg8C51XVIW3au4F7quqs9g9696o6fTnLOY5Z6vbbwINV9fvLWbbFkGQfYJ+q+nqSJwFXAi8DTqKP8zdb/Y6hk3MIK6fl7u0MVpiquhy4Z9rko4Fz2/C5DH9QK84sdetGVd1RVV9vw98FrgP2o5/zN1v9urJSwn0/4LaR8Y30dzIK+FySK9utGXq0d1Xd0YY3AXsvZ2GWwBuTfKN126zILovpkqwBng1cQYfnb1r9oKNzuFLCfXvwwqp6DsOdNE9pb/27VUN/4GO/T3D+PgD8BPBTwB3AHyxvcSaXZFfgk8CvVdUDo/N6OH8z1K+rc7hSwr372xlU1e3t913AnzB0RfXmztbfuaXf865lLs+iqao7q+qHVfUj4H+xws9fkscxBN/HqupTbXI352+m+vV2DldKuHd9O4Mku7QPdkiyC/BvgKu3vdaKdDFwYhs+EbhoGcuyqLaEXvNLrODzlyTAOcB1VfWekVldnL/Z6tfTOYQVcrUMQLss6b38+HYG71zmIi2aJE9laK3DcEuIj6/0+iU5Hzic4VaqdwJnAn8KXAAcANwCHFNVK+6DyVnqdjjD2/kCbgb+w0j/9IqS5IXAXwPfBH7UJr+VoV+6h/M3W/2Oo5NzCCso3CVJ87dSumUkSQtguEtShwx3SeqQ4S5JHTLcJalDhrtIcnySzy3Dfl/Q7jD4YJIVeZ+S+Zp+jJNUkqfNsuxlSV63yPs/oB3nHRdzu3rs8lLI7Uy7l8ZNwOOq6uFlLsulwMVV9b7lLMc4knwE2FhVbx9z/QIOqqoNM8y7DPijqvrgRIXUds2W+zJLsiTPsV3ufc3TU4DFeLbuonoMHifNwPO0bYb7EmgP3nhLexjAvUk+nGSnNu/wJBuTnJ5kE/DhNv317UEk9yS5OMm+I9urJG9KcmOSu5P8XpId2rwdkrw9yS3tARLnJXlym7emrXtykluBvwQub5u9r71Nf16Sk5J8cWR/z0/ytST3t9/PH5l3WZLfSfKlJN9N8rkke23jWMxYryQ3AE8F/qyV4wmzHMffbHfpuz/JJ7Ycx3kesze0bp/7kry/fe18tnJWklOSXA9c36Y9M8NDKe7J8KCYY9r0dcDxwGmt7H/Wpp+R5IZ2XK5N8ksj29/qGM/DTyT5apIHklyUZI+2ncOTbJzhOB3Zhg9Nsr6td2eS97TpW14Lq9r4Ns9jksOS/N927P42yeHT6nJjW++mJMe36U9L8lftXN2d5BPbON7/O8mmtuzlSZ41Mm/nJH/QXtP3J/limzbT63mssm4XqsqfRf5h+Ory1Qw3O9sD+BLwjjbvcOBh4F3AE4CdgRcBdwPPadP+G3D5yPYK+ELb1gEMDy55XZv3WmADQ1DuCnwK+Gibt6atex6wS9vXlmmrRrZ/EvDFNrwHcC9wAsOtEI5r43u2+ZcBNwBPb9u7DDhrluMwV71uBo6c4zh+Fdi3les64A3z3HYBnwZ2a8dsM3DUNvZVwCVtPzu343Ub8Jp2HJ7d9ndwW/4jW87pyDZe0cq6A/BK4CGGh0JsdYxH9ve0WcpyGcON8Q5p5fgkQzcNDK+fjTMcpyPb8JeBE9rwrsBh014Lq+Y6jwy30/4O8JJWlxe38alWngeAZ7Rl9wGe1YbPB97W1tmJ4U6nsx3v1wJPaufuvcBVI/Pe38qzH8PtRp7flttSh9HX81hl3R5+lr0APf60P7Y3jIy/BLihDR8OfB/YaWT+OcC7R8Z3BX4ArGnjxUgwAb8CXNqGLwV+ZWTeM9q6q0b+GJ46Mn+rP/I27SR+HO4nAF+dVp8vAye14cuAt08ry2dmOQ5z1etm5g73V4+Mvxv4Hws4Zi8cmX8BcMY29lXAi0bGXwn89bRl/idwZhv+CNPCfYZtXgUcPf0Yj+xvW+F+1sj4we01syNzh/vlwH8G9pq2zFbnfVvnETid1kAYmf9ZhpuF7QLcB/x7YOdpy5wHnA2sXuDfy26tbE9mCOh/AH5yhuW21GH09TxWWbeHH7tlls7ow0VuYWjRbbG5qv5xZHzftgwAVfUgQ+tj9IEks21vq3Xb8Cq2fpDC6Lpzmb69LdscLcumkeHvMQTrnNuapV5zmW1f89n2jOtmeG7mg+3nZ0aWGT1OTwGe297q35fkPoaumH8+W0GT/HKGZ29uWf4QhpuLjWP6+X7cPLd1MkNr/FutS+2l21h2tmP7FOAV0+r+QoZ3IQ8x/ON7A3BHkj9P8sy23mlAgK+2Y/zamXaaZMckZ7UurAcY/jnR6rcXQ6v/hm2Ue/p5Gqes3fMDiaUzev/5A4C/HxmffonS3zO8SIH/f9vfPdn6nvX78+MPH0e3t9W6bd7DDHcrXD3D/ua6PGr69rZs8zNzrDfntmap17jG3nZVPWu2WSPDtwF/VVUvnseyJHkKwz3AjwC+XFU/THIVQ9iNY/rr5wcM3UIPAU8c2e+ODF0QQ6GqrgeOy/CZzL8DLkyy5wL3fRtDa/j1M82sqs8Cn02yM/AOhnr/TFVtAl7fyvVC4PNJLq9HXhH0KoZH9h3JEOxPZuj6S6vjPzI8NONvZynf9PO04LLOXvV+2HJfOqckWd0+CHsbMOuHSwx9la9J8lMZPlj8XeCKqrp5ZJnfSrJ7kv2BU0e2dz7w6xnudb9rW/cTNftljpsZbnP61Fnm/wXw9CSvSrIqySsZugU+PWeNx6vXuJZy2zDU9+lJTkjyuPbz00n+RZt/J1sfw10YQmczQJLXMLTcx/XqJAcneSLwX4ALq+qHDJ+37JTkFzI8cOLtDP3RtP2+OslUDQ+cuK9N/tH0jc/hj4B/m+TnWit7pwwf5K5OsneSo9s/039ieFD4j9q+X5FkS4PiXobjMdO+n9TW/Q7DP6rf3TKjlftDwHuS7Nv2/7zM8IH7JGXdHhjuS+fjwOeAGxneYr5jtgWr6vPAf2L44OwOhlbLsdMWu4jhKe1XAX/O0OcMwx/CRxn6Wm9iaPX86jb29T3gncCX2tvYw6bN/w7wUuA3GP74TgNeWlV3z1nj8eo1lqXcdtv+dxkemnIsw7uETfz4Q3AYjv/B7Rj+aVVdy/BYti8zBP+/ZPggfVwfZejX38TQTfGmVq77GfrHP8jwLuUhhmcKb3EUcE2SB4H3AcdW1T8sZMdVdRtDy/qtDP+sbgN+iyEvdgDezHBM7gH+NfAf26o/DVzR9n0xcGpV3TjDLs5j6Gq6HbgW+Mq0+b/JcK/1r7V9vItZsmqCsnbPLzEtgSQ3M1zN8vlF2t6sX3iRpJnYcpekDhnuktQhu2UkqUO23CWpQ4a7JHXIcJekDhnuktQhw12SOvT/AIQTsNQtiT6LAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(df[\"INDUS\"], bins=30, kde=False)\n",
    "plt.xlabel(\"proportion of non-retail business acres\", fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "频率表 value_counts()\n",
    "默认情况下，频率由高到低排列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    471\n",
       "1     35\n",
       "Name: CHAS, dtype: int64"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['CHAS'].value_counts()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "条形图 countPlot\n",
    "频率表的图形化表示\n",
    "\n",
    "seaborn中有一个函数，barplot(),barplot()绝大部分情况下表示以某个类别特征分组的数值变量的一些基本统计数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Number of occurences')"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#离散型/类别型特征的分布可用countplot（纵轴为样本数目）\n",
    "sns.countplot(df['CHAS'], order=[0, 1])\n",
    "plt.xlabel(\"Charles River\")\n",
    "plt.ylabel(\"Number of occurences\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "条形图countplot和直方图distplot看起来很像，都用于观察特征的分布，不同点：\n",
    "\n",
    "1. 直方图用于查看数值变量的分布，而条形图用于类别特征。\n",
    "2. 直方图的X轴是数值；条形图的X轴可能是任何类型：数字、字符串、布尔值。\n",
    "3. X轴是笛卡尔坐标轴；条形的顺序没有事先定义。不过条形经常按照高度排序，也就是值的频率。如果是有序变量，条形通常按照变量的值排序。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(df[\"NOX\"], bins=30, kde=False)\n",
    "plt.xlabel(\"nitric oxides concentratio\", fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "一氧化碳看起来没有什么规律"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(df[\"RM\"], bins=30, kde=False)\n",
    "plt.xlabel(\"average number of rooms per dwelling\", fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(df[\"AGE\"], bins=30, kde=False)\n",
    "plt.xlabel(\"proportion of owner-occupied units built prior to 1940\", fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(df[\"DIS\"], bins=30, kde=False)\n",
    "plt.xlabel(\"weighted distances to five Boston employment centres\", fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.countplot(df[\"RAD\"])\n",
    "plt.xlabel(\"index of accessibility to radial highways\", fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "特征如果是整数的话可以用coutnplog来画，并且是按照从小到达的顺序排列的，如果是浮点数的话按照直方图的方式来画，当然对于都是整数的特征值，也可以按照直方图来画"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'index of accessibility to radial highways')"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(df[\"RAD\"])\n",
    "plt.xlabel(\"index of accessibility to radial highways\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(df[\"TAX\"], bins=20, kde=False)\n",
    "plt.xlabel(\"full-value property-tax rate per $10,000\", fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BktQzFCRJPUNBktQzFCRJPUNBktQzFCRJPUNBktQzFCRJPUNBktQzFCRJPUNBktQzFCRJvT2mQ7zZd/354DWmXv6SwWtI0iTtcqGQ5BjgrcDewHuq6owJN0mSBnfnW64cdP0HnXzUkpbbpQ4fJdkb+FPg2cBjgBclecxkWyVJK8cuFQrAUcCmqvpCVd0DfAgY9mEFkqReqmrSbeglOQ44pqp+tY2/FPjvVfWqkWXWA+vb6A8Dn9/BcquBr+5Ec3fGpGr7mVdG7ZVWd5K1d9fP/ENVNTXfjF3unML2VNUGYMPOrifJTFVNL0OTdpvafuaVUXul1Z1k7T3xM+9qh4+2AIeOjK9p0yRJY7CrhcI/AkckOSzJA4HjgQsn3CZJWjF2qcNHVbU1yauAT9Jdkrqxqm4cqNxOH4LaDWv7mVdG7ZVWd5K197jPvEudaJYkTdaudvhIkjRBhoIkqbciQiHJxiR3JblhZNqZSW5Jcl2SjybZb4y1/6DVvSbJp5I8fBx1R+b9ZpJKsnocdZOcnmRL+7zXJHnOctddqHab/ur2u74xyR+Oo26Svxz5vF9Kcs1y112k9uOTXN5qzyRZWv8GO1/3cUk+l+T6JH+VZN8B6h6a5JIkN7Xf52vb9AOSXJTk1vZz/zHWfkEb/26SZb9EdJG6w2zDqmqPfwE/CRwJ3DAy7ZnAqjb8JuBNY6y978jwa4B3j6Num34o3Yn8LwOrx/R5Twd+a0K/56cBnwYe1MYfNq7vemT+HwNvGONn/hTw7Db8HODSMdX9R+Cn2vCJwB8MUPdg4Mg2/P3AP9N1ifOHwOva9NcN8f95kdr/je5G2kuB6THWHWQbtiL2FKrqMuDrc6Z9qqq2ttHL6e6JGFftb42MPhRY9rP989Vt3gycOkTN7dQd3AK1Xw6cUVV3t2XuGlNdAJIEeCFwznLXXaR2Adv+Sv8B4F/HVPdRwGVt+CLg+QPUvb2qrm7D3wZuBg6h6w7nrLbYWcCx46pdVTdX1Y72rLAzdQfZhq2IUFiCE4FPjLNgkjcmuQ14MfCGMdVcB2ypqmvHUW+OV7Xd3I1D7Nov4lHATyS5IslnkjxpjLUBfgK4s6puHWPNk4Ez27+vPwJeP6a6N/K9vspewH+9EXXZJVkLPAG4Ajioqm5vs+4ADhpj7bFZpO6ybcNWfCgk+T1gK3D2OOtW1e9V1aGt7qu2t/zOSvIQ4HcZUwDN8S7gcODxwO10h1PGZRVwAPBk4LeBc9tf7+PyIgbaS1jEy4FT2r+vU4D3jqnuicArklxFd5jjnqEKJfk+4Hzg5Dl73lR3PGWwa+0Xqz2kheou9zZsRYdCkpcBzwVe3P4hTcLZDLCbPY/DgcOAa5N8iW5X8+okPzh04aq6s6rurarvAn9G1xvuuGwGPlKdK4Hv0nUkNrgkq4BfAP5yHPVGnAB8pA1/mDF931V1S1U9s6qeSBeE/zJEnSQPoNs4nl1V2z7nnUkObvMPBpb9MOEitQe3UN0htmErNhTSPcznVOB5VfUfY659xMjoOuCWoWtW1fVV9bCqWltVa+k2lkdW1R1D1972n7X5eeA+V0QN6GN0J5tJ8ijggYyvV8ufBm6pqs1jqrfNvwI/1YafDozl0FWSh7WfewH/E3j3ADVCt+dzc1X9ycisC+nCkPbzgjHWHtRCdQfbhi33mfJd8UX3V8vtwP+j2xieBGwCbgOuaa9lvwJokdrn020YrwP+iu6k0eB158z/EsNcfTTf5/0gcH37vBcCB4/xu34g8Oft+74aePq4vmvg/cCvD/XvepHP/FTgKuBaumPPTxxT3dfSXRnzz8AZtB4TlrnuU+kODV038n/3OcCBwMV0Afhp4IAx1v759h3cDdwJfHJMdQfZhtnNhSSpt2IPH0mS7stQkCT1DAVJUs9QkCT1DAVJUs9Q0C4pycOTnNeGj07y8QWWO7ndrb2ctResN6Qka5P80sj4dJK33Y/3vyzJO3aw9n5JXrEj79WexVDQLqmq/rWqjlvCoicDyxoKO6vdyXy/5wFrgT4Uqmqmql6zjE1bzH6AoSBDQcun/aV7S5Kzk9yc5Lxtf8W3ZwqsbsPTSS5tw6cn+WDrh//WJP9jZF2L3vmc5DXAw4FLklzSpj2zrevqJB9u/cWQ5A1J/jHJDUk2bOv/KMkjk3w6ybXtPYe31X9fa/+2z7Nt+Se2jvWuSvLJka4VLk3yliQzdDdxjbZz22f8e+CD7bN9ttW7OsmPt0XPoOu875okp4zusaR7XsDHWqeClyf50QW+lkNbW25Nclp77+8nOXmkPW9M65N/xBnA4a32memc2b6v65P8YnvvnyZ5Xhv+aJKNbfjEtt617Xf/Z+n6/v9Ukgcv9nvULmbIuy19rawX3V+6BTyljW+kPUeBkTuogWlaH/90z1q4FngwXZ9Et9Ft6NfS+uoHjgY+vkDN0fWupuu6+aFt/HdozzFg5A5Xujusf64NXwH8fBveh26v42jgm3T9Q+0FfI7urtIHAP8ATLXlfxHY2IYvBd65QBtPp7vD+MFt/CHAPm34CGBmvs85Og68HTitDT8duGaeOi+ju8v4wPZ93tC+67XA1W2Zvej6JDpwnt/d6LMRnk/X/fXedD2OfoWuX//jgTPbMlcCl7fh9wHPauvZCjy+TT8XeMmk/236WvprsV1ZaUfcVlV/34b/nO4hQn+0nfdcUFX/Cfxn+4v/KLrb9u+vJ9M9fOTv2x/2D6TboAM8LcmpdBvkA4Ab297KIVX1UYCq+g5Ae++V1fosSvfUtLXAN4DHAhe1Zfam2whvs1jHdxe2zwhduLwjyeOBe+m6996ep9I6Tqyqv01yYJJ96769dF5UVV9r7f4I8NSqekuSryV5At0G/p+2LbOdeudU1b10nc19BngS8Fng5CSPAW4C9m97Sz9G97s+EPhiVW37/V1F991pN2EoaLnN7Tdl2/hWvne4cp8lvuc+knySbsM2U1W/Onc23UbxRXPesw/wTrqnYt2W5PR52jDX3SPD99L9XwlwY1X92ALv+fdF1jc67xS6PnIeR/edfGc7bbk/Fvou30O3J/GDdHtwO7byqi3pHvt4DN1e2QF0DxH6v1X17SQHct/vzsNHuxHPKWi5PSLJto3mLwF/14a/BDyxDc/tKnxdkn3aBuVousc6zquqnlVVjx8JhG/T9d0P3dOnnpLkkQBJHpquZ9RtAfDVdo7huLaubwObkxzbln9QFr+S6fPA1LbPl+QBSX5kkeUX8gPA7dV1Jf5Suj2OuZ9lrs/SPZCJJEcDX51nLwHgZ9r5hwfTPX1s217bR+k25E+iexzrXHNrfxb4xSR7J5mie/zmlW3e5XQn+C9ry/1W+6k9gKGg5fZ54JVJbgb2p3vADsD/At7aTsTeO+c91wGX0G1s/qCq7s/jIzcAf5Pkkqqapftr+Jwk19EdOnp0VX2D7jkON9BtEEdD56XAa9ry/0D3l/S8quoeukB5U5Jr6Q5x/fhCyy/incAJbR2P5nt7EdcB97aT3qfMec/pwBNbO8/ge91Ez3UlXS+81wHnV9XMSNsvAc5th4Tmfrav0R12uyHJmXQhch3d+Z6/BU6t73Wz/lm6ZwNvout59gAMhT2GvaRq2aR7VODHq+qx9+M9p9MdetjeeQfthHTPOLgaeEGN99Gg2s24pyDt4dpJ4U3AxQaCtsc9BUlSzz0FSVLPUJAk9QwFSVLPUJAk9QwFSVLv/wM3btgYMIcrrgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(df[\"PTRATIO\"]);\n",
    "plt.xlabel(\"pupil-teacher ratio by town\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(df[\"B\"], bins=30, kde=False)\n",
    "plt.xlabel(\"proportion of blacks\", fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(df[\"LSTAT\"], bins=30, kde=False)\n",
    "plt.xlabel(\"lower status of the population\", fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 两两特征的相关性\n",
    "\n",
    "两两特征之间的关系搜索与要分析特征的类型有关\n",
    "1. 数值型特征--数值型特征\n",
    "    1.1 相关矩阵:两个特征之间的关系可以用相关矩阵来查看他们之间的相关性，这一信息很重要，因为有些机器学习算法(如普通最小二乘线性回归)不能很好地处理高度相关的输入变量，如果特征之间高度相关，可考虑进行PCA降维（特征层面）或增加正则项(模型层面)\n",
    "    可用DataFrame的corr()方法先计算出没对特征之间的相关矩阵，然后将所得的相关矩阵给seaborn的heatmap()方法，渲染出一个给予色彩编码的矩阵\n",
    "    1.2 散点图（scatter）将两个数值变量的值显示为二维空间的笛卡尔坐标\n",
    "    \n",
    "2. 数值型特征--类别性特征\n",
    "    散点图的数据点可以通过色彩或尺寸记性编码，以便在同一张图像中包含第三个类别变量的值，也可以用lmplot()函数的hue参数来制定感兴趣的类别特征\n",
    "    \n",
    "3. 类别性特征--类别性特征\n",
    "    通过设置参数hue,在图形中加入类别维度，除了使用图形进行类别分析外，还可以使用统计学的传统工具:列联表(contingency table),又称为交叉制表(cross tabulation)，使用表格形式表示多个类别变量的频率分布\n",
    "    可以通过查看一列或一行来得知某个变量在另一变量的作用下的分布\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f003c8bdd30>"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#get the names of all the columns\n",
    "#获取所有列名\n",
    "cols = df.columns \n",
    "\n",
    "# Calculates pearson co-efficient for all combinations，通常认为相关系数大于0.5的为强相关\n",
    "#用DataFrame的corr()方法先计算出每对特征之间的相关矩阵，然后将所得的相关矩阵给seaborn的heatmap()方法，渲染出一个给予色彩编码的矩阵\n",
    "data_corr = df.corr()\n",
    "sns.heatmap(data_corr,annot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function heatmap in module seaborn.matrix:\n",
      "\n",
      "heatmap(data, vmin=None, vmax=None, cmap=None, center=None, robust=False, annot=None, fmt='.2g', annot_kws=None, linewidths=0, linecolor='white', cbar=True, cbar_kws=None, cbar_ax=None, square=False, xticklabels='auto', yticklabels='auto', mask=None, ax=None, **kwargs)\n",
      "    Plot rectangular data as a color-encoded matrix.\n",
      "    \n",
      "    This is an Axes-level function and will draw the heatmap into the\n",
      "    currently-active Axes if none is provided to the ``ax`` argument.  Part of\n",
      "    this Axes space will be taken and used to plot a colormap, unless ``cbar``\n",
      "    is False or a separate Axes is provided to ``cbar_ax``.\n",
      "    \n",
      "    Parameters\n",
      "    ----------\n",
      "    data : rectangular dataset\n",
      "        2D dataset that can be coerced into an ndarray. If a Pandas DataFrame\n",
      "        is provided, the index/column information will be used to label the\n",
      "        columns and rows.\n",
      "    vmin, vmax : floats, optional\n",
      "        Values to anchor the colormap, otherwise they are inferred from the\n",
      "        data and other keyword arguments.\n",
      "    cmap : matplotlib colormap name or object, or list of colors, optional\n",
      "        The mapping from data values to color space. If not provided, the\n",
      "        default will depend on whether ``center`` is set.\n",
      "    center : float, optional\n",
      "        The value at which to center the colormap when plotting divergant data.\n",
      "        Using this parameter will change the default ``cmap`` if none is\n",
      "        specified.\n",
      "    robust : bool, optional\n",
      "        If True and ``vmin`` or ``vmax`` are absent, the colormap range is\n",
      "        computed with robust quantiles instead of the extreme values.\n",
      "    annot : bool or rectangular dataset, optional\n",
      "        If True, write the data value in each cell. If an array-like with the\n",
      "        same shape as ``data``, then use this to annotate the heatmap instead\n",
      "        of the raw data.\n",
      "    fmt : string, optional\n",
      "        String formatting code to use when adding annotations.\n",
      "    annot_kws : dict of key, value mappings, optional\n",
      "        Keyword arguments for ``ax.text`` when ``annot`` is True.\n",
      "    linewidths : float, optional\n",
      "        Width of the lines that will divide each cell.\n",
      "    linecolor : color, optional\n",
      "        Color of the lines that will divide each cell.\n",
      "    cbar : boolean, optional\n",
      "        Whether to draw a colorbar.\n",
      "    cbar_kws : dict of key, value mappings, optional\n",
      "        Keyword arguments for `fig.colorbar`.\n",
      "    cbar_ax : matplotlib Axes, optional\n",
      "        Axes in which to draw the colorbar, otherwise take space from the\n",
      "        main Axes.\n",
      "    square : boolean, optional\n",
      "        If True, set the Axes aspect to \"equal\" so each cell will be\n",
      "        square-shaped.\n",
      "    xticklabels, yticklabels : \"auto\", bool, list-like, or int, optional\n",
      "        If True, plot the column names of the dataframe. If False, don't plot\n",
      "        the column names. If list-like, plot these alternate labels as the\n",
      "        xticklabels. If an integer, use the column names but plot only every\n",
      "        n label. If \"auto\", try to densely plot non-overlapping labels.\n",
      "    mask : boolean array or DataFrame, optional\n",
      "        If passed, data will not be shown in cells where ``mask`` is True.\n",
      "        Cells with missing values are automatically masked.\n",
      "    ax : matplotlib Axes, optional\n",
      "        Axes in which to draw the plot, otherwise use the currently-active\n",
      "        Axes.\n",
      "    kwargs : other keyword arguments\n",
      "        All other keyword arguments are passed to ``ax.pcolormesh``.\n",
      "    \n",
      "    Returns\n",
      "    -------\n",
      "    ax : matplotlib Axes\n",
      "        Axes object with the heatmap.\n",
      "    \n",
      "    See also\n",
      "    --------\n",
      "    clustermap : Plot a matrix using hierachical clustering to arrange the\n",
      "                 rows and columns.\n",
      "    \n",
      "    Examples\n",
      "    --------\n",
      "    \n",
      "    Plot a heatmap for a numpy array:\n",
      "    \n",
      "    .. plot::\n",
      "        :context: close-figs\n",
      "    \n",
      "        >>> import numpy as np; np.random.seed(0)\n",
      "        >>> import seaborn as sns; sns.set()\n",
      "        >>> uniform_data = np.random.rand(10, 12)\n",
      "        >>> ax = sns.heatmap(uniform_data)\n",
      "    \n",
      "    Change the limits of the colormap:\n",
      "    \n",
      "    .. plot::\n",
      "        :context: close-figs\n",
      "    \n",
      "        >>> ax = sns.heatmap(uniform_data, vmin=0, vmax=1)\n",
      "    \n",
      "    Plot a heatmap for data centered on 0 with a diverging colormap:\n",
      "    \n",
      "    .. plot::\n",
      "        :context: close-figs\n",
      "    \n",
      "        >>> normal_data = np.random.randn(10, 12)\n",
      "        >>> ax = sns.heatmap(normal_data, center=0)\n",
      "    \n",
      "    Plot a dataframe with meaningful row and column labels:\n",
      "    \n",
      "    .. plot::\n",
      "        :context: close-figs\n",
      "    \n",
      "        >>> flights = sns.load_dataset(\"flights\")\n",
      "        >>> flights = flights.pivot(\"month\", \"year\", \"passengers\")\n",
      "        >>> ax = sns.heatmap(flights)\n",
      "    \n",
      "    Annotate each cell with the numeric value using integer formatting:\n",
      "    \n",
      "    .. plot::\n",
      "        :context: close-figs\n",
      "    \n",
      "        >>> ax = sns.heatmap(flights, annot=True, fmt=\"d\")\n",
      "    \n",
      "    Add lines between each cell:\n",
      "    \n",
      "    .. plot::\n",
      "        :context: close-figs\n",
      "    \n",
      "        >>> ax = sns.heatmap(flights, linewidths=.5)\n",
      "    \n",
      "    Use a different colormap:\n",
      "    \n",
      "    .. plot::\n",
      "        :context: close-figs\n",
      "    \n",
      "        >>> ax = sns.heatmap(flights, cmap=\"YlGnBu\")\n",
      "    \n",
      "    Center the colormap at a specific value:\n",
      "    \n",
      "    .. plot::\n",
      "        :context: close-figs\n",
      "    \n",
      "        >>> ax = sns.heatmap(flights, center=flights.loc[\"January\", 1955])\n",
      "    \n",
      "    Plot every other column label and don't plot row labels:\n",
      "    \n",
      "    .. plot::\n",
      "        :context: close-figs\n",
      "    \n",
      "        >>> data = np.random.randn(50, 20)\n",
      "        >>> ax = sns.heatmap(data, xticklabels=2, yticklabels=False)\n",
      "    \n",
      "    Don't draw a colorbar:\n",
      "    \n",
      "    .. plot::\n",
      "        :context: close-figs\n",
      "    \n",
      "        >>> ax = sns.heatmap(flights, cbar=False)\n",
      "    \n",
      "    Use different axes for the colorbar:\n",
      "    \n",
      "    .. plot::\n",
      "        :context: close-figs\n",
      "    \n",
      "        >>> grid_kws = {\"height_ratios\": (.9, .05), \"hspace\": .3}\n",
      "        >>> f, (ax, cbar_ax) = plt.subplots(2, gridspec_kw=grid_kws)\n",
      "        >>> ax = sns.heatmap(flights, ax=ax,\n",
      "        ...                  cbar_ax=cbar_ax,\n",
      "        ...                  cbar_kws={\"orientation\": \"horizontal\"})\n",
      "    \n",
      "    Use a mask to plot only part of a matrix\n",
      "    \n",
      "    .. plot::\n",
      "        :context: close-figs\n",
      "    \n",
      "        >>> corr = np.corrcoef(np.random.randn(10, 200))\n",
      "        >>> mask = np.zeros_like(corr)\n",
      "        >>> mask[np.triu_indices_from(mask)] = True\n",
      "        >>> with sns.axes_style(\"white\"):\n",
      "        ...     ax = sns.heatmap(corr, mask=mask, vmax=.3, square=True)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(sns.heatmap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 得到相关系数的绝对值，通常认为相关系数的绝对值大于0.5的特征为强相关\n",
    "data_corr = data_corr.abs()\n",
    "plt.subplots(figsize=(13, 9))\n",
    "sns.heatmap(data_corr,annot=True)\n",
    "\n",
    "# Mask unimportant features,突出重要信息\n",
    "sns.heatmap(data_corr, mask=data_corr < 0.5, cbar=False)\n",
    "\n",
    "#plt.savefig(\"house_coor.png\" )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RAD and TAX = 0.91\n",
      "NOX and DIS = 0.77\n",
      "INDUS and NOX = 0.76\n",
      "AGE and DIS = 0.75\n",
      "LSTAT and MEDV = 0.74\n",
      "NOX and AGE = 0.73\n",
      "INDUS and TAX = 0.72\n",
      "INDUS and DIS = 0.71\n",
      "RM and MEDV = 0.70\n",
      "NOX and TAX = 0.67\n",
      "ZN and DIS = 0.66\n",
      "INDUS and AGE = 0.64\n",
      "CRIM and RAD = 0.63\n",
      "RM and LSTAT = 0.61\n",
      "NOX and RAD = 0.61\n",
      "INDUS and LSTAT = 0.60\n",
      "AGE and LSTAT = 0.60\n",
      "INDUS and RAD = 0.60\n",
      "NOX and LSTAT = 0.59\n",
      "CRIM and TAX = 0.58\n",
      "ZN and AGE = 0.57\n",
      "TAX and LSTAT = 0.54\n",
      "DIS and TAX = 0.53\n",
      "ZN and INDUS = 0.53\n",
      "ZN and NOX = 0.52\n",
      "AGE and TAX = 0.51\n",
      "PTRATIO and MEDV = 0.51\n"
     ]
    }
   ],
   "source": [
    "#Set the threshold to select only highly correlated attributes\n",
    "threshold = 0.5\n",
    "# List of pairs along with correlation above threshold\n",
    "corr_list = []\n",
    "#size = data.shape[1]\n",
    "size = data_corr.shape[0]\n",
    "\n",
    "#Search for the highly correlated pairs\n",
    "for i in range(0, size): #for 'size' features\n",
    "    for j in range(i+1,size): #avoid repetition\n",
    "        if (data_corr.iloc[i,j] >= threshold and data_corr.iloc[i,j] < 1) or (data_corr.iloc[i,j] < 0 and data_corr.iloc[i,j] <= -threshold):\n",
    "            corr_list.append([data_corr.iloc[i,j],i,j]) #store correlation and columns index\n",
    "\n",
    "#Sort to show higher ones first            \n",
    "s_corr_list = sorted(corr_list,key=lambda x: -abs(x[0]))\n",
    "\n",
    "#Print correlations and column names\n",
    "for v,i,j in s_corr_list:\n",
    "    print (\"%s and %s = %.2f\" % (cols[i],cols[j],v))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 散点图\n",
    "matplotlib库的scatter()方法\n",
    "或\n",
    "seaborn库的jointplot方法(kind参数为scatter)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#打出来之后横轴为房间数目，纵轴为房价中位数\n",
    "plt.scatter(df[\"RM\"], df[\"MEDV\"]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(x=\"RM\", y=\"MEDV\",data=df, kind=\"scatter\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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cmDd/eFykzn06JhzEUnch5WZlSLWIv7j1HFdnCxOZWF68jMt+FTjNpXw7dlbY3PIB7L0nh83hgcJTOJlktlwi7kJycz8bGwnQ1NDgem9j1JSXmhjklNptZrZc9QHh7s99jFtXvZoW0tIr2xmX4342JhIouslRQ0PQbNlXRmriqRXrNvOXDgPs7O6lLVrHqZOa8sR3UcaqS+o6KxZ1EnVvIAFblMaAKQ818RTHNARcu82mhkCW4BpCATLNpF09+VM835j7YRY+vCHjHGOgVJKaEGRjfYjjm8kTX1iCHCHbV3Hj7w/RGKojGIiw/u0uHlvYiaVKQIRnN+/h/I9MyjrfGCiVpSYEGQwGOE7rGYgNpsuagkG2dvWmwxpeueM83nz3SHrecf3X5tB+UhtfWJZtmTfUB/K6+eaISdBZKWpCkJalbOvqzUoL8sCCdu7LmOSOW5o2YAAG4oUt89xVl0jIWMyVoibWuNzSgix+ZD2fbT8hfU4yxxIvZpmHgnUEA2LvZhHK343X4B010UIWSguSOckdCgZYfm07H5pwXNGt9lqjdRzsT9qGTCJJLJY0UzgVpCZayELJ2VOT3ADRkNDSFEm7lq3+3Z68sIenb/oEb3cPps+5bOlatnb3ZoUkxGKJrHCFWMyEK5STmgiDLZRa7uS2KPt6YySS7mGvd849lfM/MomEZXuU1wlFQ2NjsQRv7MsPg50xPkooZFrRYVK7W6kUSwuS2jHXzbP7zqe2cO6HP8DZdz8PwC9uPafois++Xvcw2BWLOplsBFkWaqLLhqHTgpTi2T3UOcazx3s8E6SInCAiz4nIZhH5nYjc5JSPE5HVIrLV+dvilIuI3Cci20TkVRGZXc76NIUDrqGyb+09lP48NuJ+zljH4daEK3iPZ2NIEZkETFLVDSIyBjuU4RLgGmC/qt4lIrcDLap6m4hcDHwZuBg4Hfi2qp5e7B6Z2/FZltLdGyucyevQAFv2HMiysg/1D3JcJJzOU6OqDMbjWVs4pz6bMWTZqewYUlX3YCeAR1UPi8jr2HEz84BznNMeAp7HzswwD1juOOWuFZFmEZnkXKcopeTLbmsKM2tqM4f7j+YynDwuQlPGPKMtuHheoqQpzfb0USgUZMb4bM+e8dGQEWMZqYiVLSLTsGO0Pwr8XlWbnXLBDn1tFpGngLtU9SXn2BrgNlVdl3OtzCCv9p07d7Lv8CB/+b1f5lnHT3zxEyQsi4SltEbrXONlcgP6BwcTdGVkg80MezCUlepsNiUiTcATwM2qeijzmNMaDusX4ZbJq9DEeF88mZ5TPFggDjtzoyjLUrbv78uah9y+vw/LGC0Vw1NBOhsEPAE8qqr/7RS/54wvU+PMVABLOrWcQ2YAWFEKTYzv6Do61VOKhey2BLlw+Tq6e83uZpXCSytbsONkXs9J9p4K5oL8IK+rHGu7EzhYyvgR3PNl37+gnfvWbE2fU4qFXKiljSWSpVTDUAa8HBydCVwJ/FZENjllfwfcBawUkeuAncClzrGnsS3sbUAfcG2pN3KbGLcsi31Hjrqj9Q7Gh4x9SbW0uWPRUNC4n1WKmlg6dMNtt9unb/oEh/utgrEvpVjrhrJx7KWWG8l+4EPNZxrKRu2uZRdiJMFXqSVIQ3WombVsQ20wqrtsEdkH9JKzQ5qPaWP01BW8rW+Xql6YWziqBQkgIutUtaPa9SiF0VRXqE59TZdt8BVGkAZfUQuCXFrtCgyD0VRXqEJ9R/0Y0lBb1EILaaghjCANvmLUClJELhSRN5wYnNurXZ9cROQHIrJXRF7LKHONJ6o2w41/8pJRKUhnm+jvAhcBM4H5IjKzurXK44dA7sTv7cAaVZ0OrHE++4EE8FVVnQl0Ajc6z7Pi9R2VgsTeEnqbqm5X1Rj2BvrzqlynLFT1Bey90jPJTA6VmTSqqqjqHlXd4Lw/DGTGP1W0vqNVkOkkSw6ZCZj8zMQMp+N3gYnVrIwbTvzTacArVKG+o1WQo56RxBN5Tbnjn0bCaBXkiONvqkyheKKqM8z4J88YrYL8DTBdRE4SkRB2TpufVrlOpVAonqiqjCD+yTtUdVS+sONv3sRO6Pn31a6PS/1+hL1RQhx7jHsddjLRNcBW4OfAuGrX06nrWdjd8avAJud1cTXqa5YODb5itHbZhhrFCNLgK4wgDb7CCNLgK4wgDb7CCLIKiEhSRDaJyGsi8j8i0pxz/GYRGRCRsRll54jIQRHZ6Hg5vSAicytfe28xgqwO/ao6S1U/iu2AcWPO8fnYk/+fySl/UVVPU9UZwFeA74jIHO+rWzmMIKvPy2Q4hojIh4Am4GvYwnRFVTcB3wS+5HUFK4kRZBVx/DrnkL3seTm2O92LwAwRKeZhswE41bsaVh4jyOoQcbYoTLl0rc44Nh94XFUtbGeHzxe5Ts3tgmUEWR36VXUWMBVbVDcCiMgfAdOB1SKyA7u1LNhtY/stvu5tVSuLEWQVUdU+bOPkqyISxBbfnao6zXkdDxwvIlNzvysiHwO+jh3KUTPU9HZ8owFV3Sgir2KL8XJsL5tMnnTKXwE+KSIbgUZs38SvqOqaStbXa4y3j8FXmC7b4CuMIA2+wgjS4CuMIA2+wgjS4CuMIA2+wgjS4Cv+HzJPNpw1xf28AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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SiDwEvE6eUYciEo867Eh7Zt5BXsk7S1w6ZybXLFuX0XI929bKzCk1NNUFWXjusdTXVNEXjlHtt9jZ1Zcy/ot3u1FbWdHWykAkwvnf/F1iDGlZih+zP89IKHYmr5iqnooTzHU6cMIoPDPvIK/kPcWzzT8G/BbLP3k63/jYe2ioDdAdivD0S9vZ2xvmrh+/khj/eQV09UbgL3dewIq2VqZO8nPGV9dQX2NN+P15RkKpQhi6RWQ1cAZu1KHbSnpFHe7IFXVYCMk7S1ji3XKFYzY9oSg3f29jwmJefOUp3P+Lv/LFi07gxu/8gRVtrQBZ9248a/HqxPO6QzYzDgmkOO3W11hYE2LGd+QU08puEpF697gGuBBnS5XVwEfcy9JTy8VTzn0E+FWuXSvyIb6n+Iq2VlRtz5ZLlYQYYdAF7crmI/D5LFbdeiYwdEB8/Hl11RYvvt7Bvr4I1z62nrMWr+ai+9fSExncIGBnVx8DA8bq9qKYLeQM4Al3HGkBz6rqKhHZRAmjDi1LCPh9zFuyjnnNM3nqplZUFUsERQlFvHcwa6gN8GZHL4Hpdcxbuo4V7ljTa2wYt9obagIEAj7mHNmQEh77H3Pfxa7uzHnL4xtrCQbN/GQyxbSyX1bV01T1FFU9WVW/7JZvU9XTVfU4Vf2oqg645f3u++Pc89tGqy4NtQGWXdfCivYdnHPPaq59bD07uvroj8To7ot4WsxTawM88MstiZbx0Cxjw0NrLK59bD3gxMtYHpb2ie841LO77+gbeiooeeuVnV19434+c0L8e1qW0FAX4O5LT2ZSwEd3KMI9P32NvQcHeOqm97L4ylNY9NzLidbroWvm8Mia19l7cCBhHe8P2dRWkTI2HIhE2B9yhgJNSblu0h2Cc3X30aid1ZFjPOyOVijj81N5EIrE+Ph3/pB4f9oR9dwx90RU4dimWlYuPINIzMYSQQQ++/5ZLArMZuObXQBU+WFfH1z/eOouadMPsWiqrSUQGPwqm2pTHYJzbRCw5+BAVk/0ibgJ/vj8VB4kRw6edkQ9n79odkqruHJhK92haEZrBI54dh+IcExDMMN6rrL8KWIECAT8zG4aDI+tq7Y8NwjYtGs/sw87xKu6wMTcBH/cO1eAs4TYcXCA3nCUmK1UV/mI2o5h86ONO/jGL7bw+0XnZd2nB2BSwKLG508J8m+qDWSIMRsHQv309A96AW3atZ+7Vr2asXtvMuNh/8gcTMyNAqJRm137Q+zpGWBytY9wDG58/A8ZrWCu1uh9X1/juR95IUyqCvC3fZnbseQKk5iIW6+M6xbStpVX3z7Agu86f9DffvE8rl6W2eI8dVMrPiFra5Q88Z2rRRsKr93XhhL3ON56ZeK1kJ294YQYAWJZlg9Vleqgz7M1qqu2Uq7N5nSRD8MJpZ1oO2OM60+anrYj2/Kh3xJe2dHNSTPrU4yWumqL7r4Yv190XmLMlx4aO45bsLIwrldY0xO2/2jjDs/JbcuCI5sms3bLXhSor/Gxry/CPz2wlvWvd6DA8Ycd4jhRVFclnlfoDrqGoRn3Y8j01G/fX9hKLOZ03+Ja2Svad7Dq1jPpHRi0gjdu7yQUtnnX4fUZ3fjsJmfecZxbwcVm4o0hkxO2h8JRXn27h1hMOfueNSnX3XPFyfzdI0Zm6qSqFMGlTEwH/BNynrDYjOsuGwbTdtQE/Ny9ahM2md7eZ85q8lwRGUpwheRFNORHMd3PjhCR1SKyyQ3y+qxbPlVEXhCRLe7PKW65iMgDbpDXyyIyoqRN6cR9I8PRWEaummybTg0lOJMsc/Qp2hhSRGYAM1R1o4hMxglluAy4Edinql8TkS8BU1R1kYhcAtwKXAK8F7hfVd+b63cMJwvD7p5+9oci1FVXISj9EZtJAZ/nWHDVrWd6duXxMSQYK3sEeHYjJTNqRORHwIPu61xVfcsV7RpVnS0ij7rHT7vXvxa/LtszCxGkl4Gz+MpTeGLtG3zl8pPZfSBzr/CZ9UFESDF2aoMW+0MxI76RUz6jxo2xPg1YD0xPEtnbwHT3OBHk5RIPAEsR5HAzecVzWzfVBblj7omJYK6vXPZuGmuD1AerUuYgk9ep6yclT/GMzBXMtKi5Kfo3ISJ1wHPAbap6IDmyVVVVRApqolU1ka+7paUl73vD0RhNdcEML59H5zfTWBckEPBzeA5HidFwBZuI/o2FUlQrW0SqcMT4PVX9X7d4t9tVx8eZe9zyRGo5l+QAsBET8Pv4zAWzEmIER1QLlrfT2Tu05/ZoTPFkE7XZRGCQYlrZghMn82pasvfkYK70IK/rXWu7Fdifa/xYKA21AY5urPUUVTgaG/L+0ZjiMfOWQ1PMFvIs4DrgfBH5k/u6BPgacKGIbAHe774H+AmwDdgKLANuGc3KWJYwKejzFFXAP3S+mtGY4jHzlkMzrpcO0/GytJdd38Ls6ZPzSro+UoPEjCFTKO+0TzEYTmo521Y6e8OEozECfh8NtYG8xDhaGCs7wcRby/YivpRYLiaaf2OhjPu1bMPYYkx32SKyF9hexio0krY72xihEurdoaoXpxeOaUGWGxHZoKot5a5HoVRyvU2XbagojCANFYUR5MhYWu4KDJOKrbcZQxoqCtNCGioKI0hDRWEE6YGIXCwir7nxPV/yOH+jiOxNchr5ZNK5G9x4oS0ickP6vWWu971Jdf6riHQnnYslnXu+lPVOQVXNK+kF+HDSlxwDBIA/AyemXXMj8KDHvVNxPJamAlPc4ymVUu+0628Fvp30/mC5v3tVNS2kB6cDW9XZejoMPIOT1CkfLgJeUNV9qtoFvABkrEYUiULrfTXwdElqVgBGkJlki+1J50o3XHeliMQ93fO9txjk/btF5EjgaOBXScXVIrJBRNaJyGVe95UCI8jh8WPgKFU9BacVfGKI6yuNq4CVqprsKn+kOsuJ1wD3icix5aiYEWQmQ8b2qGqnutkjgMeA5nzvLSKF/O6rSOuuVXWn+3MbsAYnSrT0lHsQW2kvHB/RbThdWtw4OCntmhlJx5cD69zjqcAbOAbNFPd4aqXU273uBOBN3EURt2wKEHSPG4Et5DCIivkynqJpqJP489PAz3As12+r6isi8mVgg6o+D3xGRD4MRHGSPN3o3rtPRO4G4ukevqyq+yqo3uC0js+oqz6XdwGPioiN02t+TVU3laLe6ZilQ0NFYcaQhorCCNJQURhBGioKI0hDRWEEaagojCBLjIioiHwj6f3nReTOpPdtIrLZfb0kIme75T4RaReRc5Ku/bmIfLSkH6DIGEGWngHgChFpTD8hInOBBcDZqnoCsBB4SkQOU2eZ7xbgQRGpEpGrAVtVv1/KyhcbI8jSE8WJafmcx7lFwBdUtQNAVTfirJN/yn2/HngRuBP4L+DTJahvSTGCLA8PAdeKyKFp5Sfh7MWezAa3PM7twG3AU6q6tXhVLA9GkGVAVQ8ATwKfGcbt5wD7gZNHtVIVghFk+bgP+ARQm1S2iUHPoTjNwCsAIlIL3AOcD0xz99scVxhBlgnX6eJZHFHGuQdYLCINACJyKo7jxhL3/L8Dz6rqZhwD514RqS5ZpUuA8fYpL98gyTBR1edF5HBgrZsMoAeYr04KlZNwXN3e4177RxH5GY4hdFfpq14cjLePoaIwXbahojCCNFQURpCGisII0lBRGEEaKgojSENFYQRpqCj+H4gmKxXmTvonAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Cx5nZT9tvZlhceO3nh0Bv3WROJJ1G3XQuM3uT8jT2mxfI6ybgS3EYGRoXXpux8qyLi4DzKt0pzwN/Q3kGcT3fBlZL+o158vqemT0Rn7Xh8NkpThD8jecEwYXnBMGF5wTBhecEwYXnBMGF5wTBhecE4f8Bc/GF6NzLgMUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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WJRNuEm99+12+/uA24+ONb5jpwhs/YtHRGuM7559ELBJi/WOvs+6sJXS0RCc8mGf9ytP4n9/t5OOndnDs3Gb2jYzmMkrmNjaMycJoa4qwfd/wmGOMT6naeHEXi1qbPIOKBXOjRCVcb6KDWvbx+oZSOUFAxpe6+r4t9A+N8unOo7lyc4/ng3muuudFzu9awNq7exgYTXNUS4wF8WaOaollsjDyHtRzIJWecIwr3BT7bPnyu7oLpocPjjj1KLqizPhPo9CIRVMkRBOhogFFNgBJ2ekpHWN8SpUJKspnxp/xCo1YDKfSuVGLQs5+NgCJhIsv2VZsVCS/bIKK8glEeCJyjoj8UUReF5FDWrPWa8TiO+efRGtzA/f3vJUbeRg/YrF+5Wnc1/1nNl7URbzEA3q8jnHbqk7u73krV954cVfBhwO1NdVXylM5BJH6HgJeBc4GeoEXgAtVdWuhbcqOakfTWDI2qs1O2LZth92DSUbTmYnaDSEBhLZZUawyzkiOo/QNpSYd1bY1RYhGZ7xHM1WqKjvlfcDrbiYyIvITMgsoFxReKSxLOHx2Y9E+4bDFUS2xon1KHaN9dnRM3fgyQDQaZn79Cq1sgrjUzgfeyiv3unVjmMq8WsPMoWp/mvnzakVkj4i8GaA5bUBZj9uoMoK2+1eqeo5XQxDC2wkcnVfucOsKoqrtvlpUAhHpLvVgoWqkmu0O4lL7AnCciCwSkQiwgswCyoY6IojpjbaIfAF4CAgBm1T1D5W2wxAsgfh4qvpL4JdBHHuKbAjagClStXbPiCQBQ+0x44fMDDMTIzxDINS18EqNGYvIavce4kvu67K8tktE5DX3dUmV2X1jns2visj+vLZ0XltwdxNUtS5fZCLqPwGLgQjwO2DpuD6rgVs8tp0LbHf/trrvW6vF7nH915G5c5AtDwb92atqXZ/xcmPGqpoCsmPG5fBR4BFV3aeq/WSe8ed5h94HJmv3hcCPK2LZJKhn4ZU1Zgx8WkS2iMh9IpIdcSl3Wz8o+9gishBYBPw6r7rRHQN/VkQ+6Z+Zxaln4ZXDL4BjVPUkMme1OwO2Z7KsAO5T1fwU64WaGUb7LHCTiBwbhGH1LLySY8aq2qeqSbf4faCz3G19ZDLHXsG4y6yq7nT/bgceB06dfhPLIGgnM6gXmVGb7WQuRVkn/cRxfeblvT8PeNZ9Pxd4g0xg0eq+n1stdrv93gPswB0kcOtagaj7vg14jSKBiZ+vqk2L8hstMGYsIt8AulX1AeCLIvJxwAb2kYlyUdV9IvJNMgkPkHl4+L4qshsyZ7ufqKsylxOA20XEIXO1+7YWyfz2EzNkZgiEevbxDAFihGcIBCM8QyAY4RkCwQjPEAhGeD4hIioi38sr/4O7YGC2vEZEXnFfz4vIB9z6kLuc6pl5fR8Wkc9U9B/wGSM8/0gCnxKRtvENInIusJbM8qnvAa4AfiQiR2pmeOsq4BYRaRCRCwFHVf+zksb7jRGef9hk5jx8xaPtGuBqVd0LoKovkhkH/rxbfg54BrgO+BbwhQrYW1GM8PzlP4CVInLYuPoTgZ5xdd1ufZZrgS+TWd3ydf9MDAYjPB9R1QPAXcAXp7D5mcC7wF9Oq1FVghGe/9wEfA7IX4x2KwczXbJ0An+A3GLSNwAfBg4XkY9VwM6KYoTnM27ywE/JiC/LDcD1IhIHEJFTyCQgrHfb/wX4qaq+QibQuFFEij8Oa4ZRt9kpFeZ75AUIqvqAiMwHnhYRBQaAVaq6S0ROJJOCdbLb939F5CEyAcnXK2+6P5jsFEMgmEutIRCM8AyBYIRnCAQjPEMgGOEZAsEIzxAIRniGQPh/Tj05bOKus6QAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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5XAUnvNToRSKFPZ3jkHAyekcU0uH3euydC2/BXaZhwymHq6BtvLsu/xITR1Um7TG/VwhHle5oDL/Xg1cgpvGLF+qO4fMKo21emqam0Hs9wm/WfcCvXvswGeE4YdyIAdt4g00XyjecsvEKTngQF19bV5iPPu3skw71v1v2cuEpE3hmy16+OmUcD637gG+feWwyBaq3kFJT6FMv7LgRASIxGFtVNijRZUgXKiiGEPEoHucCwOMRW4fiew9v4vL6o1hkfS5Zs5XLpk/k5ie2cu2sSfE0+V4D8qSm0CeOk0iFP7I6OChv9sAhe4P8wKH8TUXvj8QgR+mcssFQkMKD9EZvwtFIfCbS4quD/uQ+qc6CEw6FiYBkpmCFl87oTTgaic9ESlRqClSqs+CEQ2EiIJlxRXgiMkdE3hWR90VkUHPWjq0q6xNluG/uaTyx8SOWWZ+3X3Yyaxr2cOflJ3P/y39JOgup6UZjq8q43yZlaigpSUNJFyoV3Eh99wLvAecCjcAbwNWquj1dnXQduru7ozS1d/XwaiNRxecTuiOKCAiC1yN0dkfxeT22zkLCq41EY2n3GSjF4tUOkbxKff8y8L6q7gIQkUeJT6CcVnjp8Pu9w5Ku5PN5OLI6mHnHAVBW5mNC6Qkta9x41E4A9qSsN1plPcjUr9ZQ2OTtTzK1X62INIvIbmvTaGDQQ1+UEPlwnZ5T1Tl2G9wQ3l5gYsp6nVWWFlUdk1gWkY2ZBvkx5P91cuNR+wYwWUSOFZEAcBXxCZQNJUTO73iqGhGR64DnAS+wUlXfznU7DO7iio2nqs8Czw6y+vLhbEsRk9fXqSCSBAzFR8GGzAyFjRGewRUKSnjDEeMtNkRkooisFZHtIvK2iCy2ykeJyIsistP6rHG7rakUjI03mBhvKSAi44HxqrpJREYADcDFwALgU1W9zfqR1qjqEheb2oNCuuMlY7yqGgYSMd6SRlX3qeoma7kN2EE8BHkR8JC120PExZg3FJLwsorxljIicgwwDdgAjFPVfdamT4iPS5g3FJLwDP0gIlXAGuBGVf08dZvG7am8sqkKSXgDjvGWCiLiJy66h1X1Sat4v2X/JezAJrfaZ0chCc/EeG2Q+Ji+DwA7VPXnKZueBuZby/OBp3Ldtv4oGK8WQEQuAO7hcIw362FsixUROQt4DXgLSPRQ+gFxO+9x4ChgN3CFqn7qSiNtKCjhGYqHQnrUGooIIzyDKxjhGVzBCM/gCkZ4BlcwwhsGRKTd+jxGRFRErk/ZtlREFljLD4rIByKyRUTeE5Ffi0hd7+OkrC8QkaXW8hQReVlENovIDhHJ6wzjTBjhDT9NwGLrJbcdN6vqKcAU4E3gD/3sm8ovgLtV9VRVPRH45fA01x2M8IafZuAlDkcNbNE4dxMP4P9NFscdTzwxIlH/raE00m2M8JzhduCfrRzCTGwCTshiv7uJ3x3/T0RuEpHqIbXQZYzwHMAaF2YDcE0Wu2cau0ytY64CTgR+C8wC1ovI8M2yl2OM8JzjZ8ASMgtrGvHkTYBQL3tvFCnDUKjqx6q6UlUvAiLAXw1je3OKEZ5DqOo7xEfA+obddolzA3HbLTFR9CvAPGt7ELgCWGutz7HSnxCRLwC1FHBamBGes/yUeN5gKneKyBbi/UdOB2ZbqfwAi4FLRWQzsB74raq+am07D9hm1X2euHf8iePfwCFMdorBFcwdz+AKRngGVzDCM7iCEZ7BFYzwDK5ghGdwBSM8gyv8P4ja40RpngUvAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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n3e6jjO1rrDzskrTbulK9r7mt6fbWJmqJvog30s9RrKrrRWTk7t6oqq8Bh/mcfx84opxJVhOme4qZjBvXEvcl1DgXQVNZZeUrH3kSPC845rOOcaYx3aJf0L3G8/g3DQlaC/RFvO5+vjYoYLqnmOm47T1Z7iikbRUJcMdT7+YLv0vCXOmszd2/Xs/dv17vmM85Rzkzi5vjFovnzfDUZjTHnaRPxvz9gk2u0Jpp5nMt0BfxPicir/mcF2C/KsynpjA1Lsw3OjEr/BbwlWRuKEJz3HKsycBGfUKgfpLspxcf5RgTVEgeq0O2S19X/Bxwos/jBOCg6k6t+jD1C5qOMy38Llq17iIet5+xO53jqkde572OTjp2pnivo5OrHnndE/rrCfjH6HEljCbjwpJ5MxzXXTJvBsl47Q2MviReUlXfBhCRhKr2Zj6KyGyg3z6+RoBpSrupcWFa+G2rfxHPPq4inng0wsnT9+Bze47EVmXP0UlOnr6Hh/CmdcRdKZu3Pv6Lwy/4/LoOxrTEaXMmxVQdfRHvP8i7TwB+W/IcYLHreMjC1D1T3DfDo8pchkhL3OIbriKexfNm0OJau41KRJi571jOvucFh7EyKuEkXnPCYsn8mR6jxl0U1JKIcOBeozhz6QvO6yYazIGMM5/KLY8Hd14O5aVPmbhnElHxJYDbV5bKKnc+vc5hhNz59Dr+4eRDHOM6dqV9jZXrTzyYifFPf7psDuIRHGvBnJ3DHQnrSvs7uFcsPJLRDSbxNOC53/GgQ1D61PIFsz37XJgkE3T25HzdJOccta/H4XvBF/bjykde7SXoradP96hkEfjOVw8gakWwBNpbE3znqwd4Ihw5W9m6K8NVj65x/AONcpVpBtV6ZHPe4qFqN3rsi3iTROR2CoZY4TmFY9/g/mCCaSjMNPtDBI6ZOsGhQv1CYar0kq54zSsfeZUVLn9aPGKRzir/66GXHKrRXXORtf2zXdz+uXLao1U7faovq/Yq8rvvrC55Xjy+uiIzqCOsgBYW7loK0+wPDbBq3ZGrjGFEwrTVRVBiqduBPK4lzhLXxi5+Du5abEPaV5LAsopdqcYwy7MzC9abZn/kNCCC4GJeUETCnVhqGvs1dSBvLawR3WvGG7/5eSaUjE3VIH2qrySBJ3b3uqqeVLGZVBCmqkID3Bru3iTJgIxhd/ZHImL5jnOrRtPN+8ohqJ+qXeFK2+rJ+PeA+ftvOAll6uAeCPpa4x0J/Il8gc+LDBJL1jTPrrXJ8m0l0drkXUPd95wzm+S+5z7gH0/5vGNcToMI4FxrpXK27+Z9PzzrUMc4K0Aiu5dZpkZDxBLfJAaPWygivuWXMbdjcADoi3h7kE9nOot8uvp/ki9zfLNiM6gCTENcnT22WdqRHWCFulReNhewdnOFLiwR3xoO99rSNkyfMpWMTVHLty9fk8vPqAp/6co43Ey3zZ3OqKbKbfLX1xovBzwJPCkiCfIEfFZEblDVOys2iwpjoPlz7kW+HWCFujOQI2UQYMm8Gb0NeYqhKzcBElGL735tKhu29eTvK5I/dmfGRC3h388+jK0lNSFjWmIe1Z21zfyHWVt9M67dCa0DgUmxT4L8DoxnAZOB28mnsTcsTENcpmlHpjUSQcaKWzWmczZ3uAhwx9PrWHSSlwB+kmekS/LYqvQUmgqVSmSPW0iVS+dMYXNn3jqNRywunTPF4z8sp0qvv/6+voyLB4BDgF8AN6jqG31+YgPANMSVCJA8boliWiMRpBr/t0s1ZnIasMh3EjlI8rj9c0ES2S2hoiJ0prKeSM0EV0TGNItlIP6+vvx484Ep5GsunheRHYXHThHZsbs3ishnROQZEVlbKOi+rHB+jIisEpF1hb9tfcyhXzBpP6YIK1/dwH3nHc7TV36J+847nJWvbvCkHRU7h5b6v/ys2qaCaixasUXV6FahRUlbCj+VHJQ/5/bPmTrC0yVGUrHN233PfUDaU1WH7/26yTIQf19fa7yBJGplgStV9WURGQGsEZFVwHnAU6p6k4hcC1xLfn+zmqO9Jc78IyeTyua/eBFh/pGTPSrZtHNozlYyLuduJmt7/G6m7pS4oeQxbSpkCb75gu7/yZ5sgNV9ptPqHki5ZNXalKnqJ8Anhec7ReQt8mG2k4FjC8OWAc9SJ+LZtpLK2vxpa3cvoT4zJoltq0NCmnYOVWBHj1eVtbc6VVk6Z/P4yxsc/sN7fvU+lx63v2OcJfgS1E2UWER8M5Xd7o+gyIpbJccj/p0T3IQfSLlkTfrjichk8vUXLwITCqQE+DP5lhh+76n6Dt1bu9J07Ex5iDKyKcb4kc7iF9tWMjmbrK1IzvaQE8xjpomIxSkznGlRt5w2jYTrh+3J+hP023OcBM3k/K1Vt9vFVCVHAgjvduMNpFyy6sQTkVbgMeByVd1RuomIqqqI+Ga51GKH7nTOrPglm7V5e+NOT+/lAyeMIFqyfjNdk2UNHc2JqD9B3X30bFU6djrXVR070x5CmarkbkPCm27y54eqJtsXmvU8Bjykqj8tnN4oInsWXt+Tvpv/VA2mRNnUmeolXXHMRT9ew6ZOZytaU6MhE+BozrgczXaABHXPLxHNh/RuXLmWM5a+wI0r13L18VNJuFSeacp9ImpxwRcn9+40JCJc8MXJXsLbyrqOTube/VuOueVZ5t79W9Z1dBp1oKoa8SQ/63uBt1T130peeoJ8ITfUeYfuZMy/lsIdXDcNSTXFLN/N8ZpiZlatp2wx0J/mvI9szva1Vj15diXunuK4Zc9/4MmeiVlCOqucd99LzLn1/3HefS+Rzioxw+1KB2zVDhBHA98CXi807gH4HnATsEJELiBfszG3inPYLeJR8fXjufuTmOaxtTUn2GNUzlOp39bs9pOZGQPRgK5XboISYK26I+stTRZ/c9wBniVDiys2ncravtscuPMFG9Wq/Q3BSQXHVeu65aArlfOPIJx4sCMVfHxrgvvPP9xj/Y5v9abCm+wolLXhP1/d4MmKOfdoZ8VoNICgUR9r1SSmu7PHZmtnN8sXzO5tbfveph2Mbo45YtOmocSGt2obFRk7KILgrdxMuUJSd8+f6RljmhUzriXumxXj7Thg+1qr7kiIZQX451wLKUsgEon2bktfHOe2Vk1jzg1t1TYyTLM6NnWmWOgyLhb+eA0rFh7JXqM/FRWmqmd7T9a3NmOPY/Z3dBywDf8xbNvMP2fqxzNNxxrItg7DmnjJeITb5k7vjYcWjQF3KMzUuDBVPelszqiFRdRwbamK7/zcRoNpC4sg1b3IJWmh/9uVDmviNUcijG6JO0Jho1viNEecRDE1Lsz3uTBdGym3nj7dkwcorgI/Ef+MYXcKv2WYCBqNCpfOmeIxuqIVbGm2230uGgWl+1xUEhu2dfWud4qY1JZk+YLZTCwprc9kcry9qdNTL3vg+FbPnhOVbIL98fZuFj3xhocoi046xKHiP97exQebuzyqcb+xzY59M7Z09vDx9h4PofYa3eRoU7ZhWxc3/PxNz3WvP/Fgx/digECmDmuJZ2q9mXaBAvPGkUWPfyZnEwvw+I9vTfi6P7zWtPirRld+XyrrvxukuzYjZxgJGQiGNfFME0ErvVFy0ePfl8SLRi0OnDDCE5KKuiIIpgQ13byvKWLxva8f6Fn7umPJA8GwJl4y7t9zJBmvXBaGH8pp+x+NWg616gdTggYV+3iq1gKajbsl40AwrInXk1HWd+xwdE/6/YdbaG8Z6xhX6abV1Wj7b0LQZMy/2CfpCumV0+qi3/Ot2CcNQkQjsM/YEZ7uSe7IQKW3Ia1X2/9UJqBpj8uPF+RArmTvlMG/8ekAkMmq7w/hziIG8528TVDpjZxNEdQ6IxOQIe1OfffEiAeAYS3xghMjq3vdSktQU5gaUwKMaYl52p5VcnbDWuIlAlrMBnV+ryQqKUFN0Vwwpkol2ZL5Mz3NvGNRIZPDkRaVyeXPVwrDmnjRSIBKqWCrhkZCV9ru9UcW8/HueOpdutLOpUUqq76Jr8WiqEpgWKva7nTOt5rqzrMP8zRmHArIBSUdnOBOOjDLzB4IqkY8EfkR+e7wm1T1kMK5McBy8h0J1gNzVXVbtebQF+LRiG81VT02lasFAtOdXEHdWljd1VS19wPHu85dS76mdgrwVOG4bqiXdVkvJKL5DVtK73exT+eEWnwvVU0SKJQ1riyReO8Ax6rqJ4VCn2dVdepuPgKoXpIAVL/XbyPhwy27+Pen/8CFx+znqB776zn7s0+7c21Roe+lYZIEjGpqa4n+5pMNRkQt4fn3t7BizUe95ya1Jbnsy1M8Y6v9vdTNqi1sHR8obv126A4xMBSbFDncKT6qthaotcTbKCJ7lqjawJraWhR0DzekczZtLc4dv0FJVzAGa4paU71hamqHI+IRi627Mpy59AW+dMuznLn0Bbbuynh6NNcC1Szo/gn5baimishHhTram4CviMg64MuF4xA1gun2BbVANetqzwp4qSFqaocjTDOua4FhHTIbbogFtM5wt6aoBULiDSNEI1ZAbHroW7Uh6ojujH9s+geuTp+1QEi8YYSY5b+/RqhqQ1QVLU0Wd7ny8fy6RdUCocQbRkhlYGQywk8unI2tiiWCYpPKAJXdqqxPhMQbRkjnbM6+5yVPupO79W4tEKraYQTT1ru1QEi8YYTivhml8NtGoBYIiTeMMK414WtcjPPpbFpthGu8YQTTVhc1mUvNrxiirjBpdVELhKo2RF0wKBozikgH+a0JGgFjgc31nkQFUIv72Kyq7oIvYJAQr5EgIqtV1buHwCBDve8jVLUh6oKQeCHqgpB45WNpvSdQIdT1PsI1Xoi6IJR4IeqCkHgh6oKQeLuBiPxIRDaJyBsl5xaJyAYReaXw+Ho959gXROQzIvKMiKwVkTdF5LLC+TEiskpE1hX+ttV0XuEaLxgicgzQCTxQ0nhoEdCpqv9az7mZotCxYU9VfVlERgBrgG8C5wFbVfUmEbkWaFPVa2o1r1Di7Qaq+itga73nMRCo6ieq+nLh+U7gLWAicDKwrDBsGXky1gwh8fqHb4vIawVVXFMVNRAU2sYdBrxInTt3hcQrH0uAzwKHAp8At9Z3OmYQkVbgMeByVd1R+lpfnbuqgZB4ZUJVN6pqTlVt4B7giHrPqS+ISIw86R5S1Z8WTm8srP+K68DAzl3VQEi8MlH8sQo4BXgjaGwjQEQEuBd4S1X/reSlunbuCq3a3aDQ8epY8ilEG4HrC8eHkldN64GFJWulhoOIfAH4NfA6UGwL9T3y67wVwN7kU87mqmrNDKmQeCHqglDVhqgLQuKFqAtC4oWoC0LihagLQuKFqAtC4pUJEckVslLeEJFHRGRiSabKn12ZK3HX+J+LyGjX510uIj0iMqpw/LWS93eKyDuF5w+IyLEisrLkvd8shO7eEpHXRaSm8dYBQVXDRxkP8pkpxecPAd8pOV4EfHc345cBf+d6/UXyfrbzfa71LDCr5PhY8lt0AUwH/gDsWzjet3A8rd7fkckjlHgDw6+B/csY/1vymSEAiMhngVbg74GgLvlB+C7wfVX9AKDw95+Bq8r8nLogJF4/ISJR4H+QjwiYjI+Q32rhiZLTZwIPkyfwVBEpJ0PkYPK5daVYXTjf8AiJVz6SIvIK+R/5j+TjoCbji6lHq0peOwt4WPMJB48Bp1dhvg2JsGlP+ehW1XLapHer6qEi0gz8N/DXwO0i8nlgCrAqH8cnDnwA3Gn4uWuBmcCrJedmAm+WMbe6IZR4NYKqdgF/A1xZUNNnAYtUdXLhsRewl4jsY/iR/wr8bSG5s5jk+T0GSX5gSLwaQlV/D7xGnnRnAo+7hjxeOG/yWa8A1wA/F5G3gZ8DVxfONzzC7JQQdUEo8ULUBSHxQtQFIfFC1AUh8ULUBSHxQtQFIfFC1AUh8ULUBf8f8Wh6ZWBTAy8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 180x180 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Scatter plot of only the highly correlated pairs\n",
    "# 使用SVG格式可能导致pairplot变得非常慢\n",
    "%config InlineBackend.figure_format = \"png\"\n",
    "for v,i,j in s_corr_list:\n",
    "    #成对\n",
    "    sns.pairplot(df, x_vars=cols[i],y_vars=cols[j] )\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 402.375x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#参数hue的参数类别\n",
    "sns.lmplot('RM', 'MEDV', data=df, hue='CHAS', fit_reg=False);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    " _, axes = plt.subplots(1, 2, sharey=True, figsize=(10, 4)) \n",
    "#加入另外一个特征，打印箱型图和提琴图\n",
    "sns.boxplot(x=\"CHAS\", y=\"MEDV\", data=df,ax=axes[0]) \n",
    "sns.violinplot(x=\"CHAS\", y=\"MEDV\", data=df, ax=axes[1]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以看出，不同CHAS取值，目标MEDV的分布不同，初步断定CHAS和目标MEDV有关系。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
